GENETIC STUDIES OF DROUGHT TOLERANCE IN COTTON (Gossypium hirsutum L.) By Muhammad Sarwar M.Sc. (Hons.) Agri.(Plant Breeding and Genetics) Reg. No. 87-ag-1304 A thesis submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY IN PLANT BREEDING AND GENETICS DEPARTMENT OF PLANT BREEDING & GENETICS FACULTY OF AGRICULTURE UNIVERSITY OF AGRICULTURE, FAISALABAD PAKISTAN 2013
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GENETIC STUDIES OF DROUGHT TOLERANCE IN COTTON
(Gossypium hirsutum L.)
By
Muhammad Sarwar
M.Sc. (Hons.) Agri.(Plant Breeding and Genetics) Reg. No. 87-ag-1304
A thesis submitted in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY IN
PLANT BREEDING AND GENETICS
DEPARTMENT OF PLANT BREEDING & GENETICS
FACULTY OF AGRICULTURE UNIVERSITY OF AGRICULTURE,
FAISALABAD PAKISTAN
2013
To, The Controller of Examination University of Agriculture Faisalabad
We, the supervisory committee, certify that the contents and form of thesis
submitted by Mr. Muhammad Sarwar, Reg. No. 87-ag-1304 have been found
satisfactory and recommend that it be processed for evaluation by external examiner(s)
for award of degree.
Supervisory committee:
1. Chairman ________________________ (Dr. Iftikhar Ahmed Khan)
2. Member _________________________ (Dr. Faqir Muhammad Azhar)
3. Member _________________________ (Dr. Asghar Ali)
DEDICATED
TO
LOVING PARENTS
AND
FAMILY MEMBERS
ACKNOWLEDGEMENT
Praise to the almighty Allah for the magnificent blessings who has blessed
me with the caliber to bring this task into this shape. I revere and adore to Hazrat
Muhammad (S.A.W), who is paragon of knowledge and prodigy of truthfulness.
I would like to laud the tireless efforts of my supervisor, Prof. Dr. Iftikhar
Ahmed Khan, Department of Plant Breeding and Genetics, who tackled the whole
process and provided help round the clock for the completion of my thesis.
I offer my cordial gratitude to members of my supervisory committee, the
respected Prof. Dr. Faqir Muhammad Azhar, Department of Plant breeding and
Genetics,, and Prof. Dr. Asghar Ali, Department of Agronomy, for their kindness
and commitment in all areas.
I am pleased to note that all respected teachers and my friends have dilated
my vision with their avidness and enthusiasm.
I am unfeignedly grateful to all members of my family for their heart
warming and delving support. Specially, I would like to mention the patience of
my children
(Muhammad Bilal Sarwar, Muhammad Saad Sarwar and Muhammad Ahmad
Sarwar), who spared me for the completion of my work.
Finally, the scholarship awarded by Higher Education Commission, Government
of Pakistan is also thankfully acknowledged.
(MUHAMMAD SARWAR)
CONTENTS
Chapter No. Description Page
1 INTRODUCTION 1
2 REVIEW OF LITERATURE 5
3 MATERIALS AND METHODS 64
4 RESULTS AND DISCUSSION 75
5 SUMMARY 143
LITERATURE CITED 146
LIST OF TABLES
Table
#
Title Page
#3.1 List of crosses and backcrosses 68 3.2 Coefficients of genetic effects for the weighted least squares analysis of generation
means Mather and Jinks (1982) the mean (m), additive (d), dominance (h), additive × additive (i), additive × dominance (j) and dominance × dominance (l) parameters.
71
3.3 Coefficients of the genetic variance for the weighted least squares analysis of generation variances Mather and Jinks (1982 ).
72
4.1 Mean squares for seedling traits in cotton under normal and drough conditions. 75
4.2 List of varieties/genotypes selected after screening 76
4.3 Similarity matrix for Nei’s and Li’s coefficient of 12 cotton varieties. 81
4.4 Generation Means of various morphological and physiological traits of Cross-11(NIAB-78 × CIM-446) and Cross-2 (CIM-482 × FH-1000) under normal (N)conditions.
84
4.5 Generation Means of various morphological and physiological traits of Cross-11(NIAB-78 × CIM-446) and Cross-2 (CIM-482 × FH-1000) under drought (D)conditions.
85
4.6 Best model fit estimates for generation means parameters (± standard error) by weighted least squares analysis of various morphological and physiological traits for cross-1 (Niab-78×CIM-446) and cross-2 (CIM-482×FH-1000) under normal conditions
86
4.7 Best model fit estimates for generation means parameters (± standard error) by weighted least squares analysis of various morphological and physiological traits for cross-1 (Niab-78×CIM-446) and cross-2 (CIM-482×FH-1000) under drought conditions
87
4.8 Components of variance, D (additive),H (dominance), F(additive× dominance), E(environmental) and narrow sense heritability and genetic advance estimates of various morphological and physiological traits for cross-1 (Niab-78×CIM-446) and cross-2 (CIM-482×FH-1000) under normal (N))conditions.
97
4.9 Components of variance, D (additive),H (dominance), F(additive× dominance), E(environmental) and narrow sense heritability and genetic advance estimates of various morphological and physiological traits for cross-1 (Niab-78×CIM-446) and cross-2 (CIM-482×FH-1000) under drought (D))conditions.
98
4.10 Genotypic (upper value) and phenotypic (lower value) correlations for different plant traits in cross-1 (NIAB-78 x CIM 446) of cotton under normal conditions.
132
4.11 Genotypic (upper value) and phenotypic (lower value) correlations for for different plant traits in cross-2 (CIM 482x FH-1000) of cotton under normal conditions.
133
4.12 Genotypic (upper value) and phenotypic (lower value) correlations for different plant traits in cross-1 (NIAB-78 x CIM 446) of cotton under drought conditions.
134
4.13 Genotypic (upper value) and phenotypic (lower value) correlations for differentplant traits in cross-2 (CIM 482x FH-1000) of cotton under drought conditions.
135
LIST OF FIGURES
Figure Description Page
4.1 Frequency distribution of the F2 for plant height of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
103
4.2 Frequency distribution of the F2 for monopodial branches of cross-1 (NIAB-78×CIM-446) of Cotton under ( a ) normal and ( b ) drought conditions
104
4.3 Frequency distribution of the F2 for sympodial branches of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
105
4.4 Frequency distribution of the F2 for Bolls/plant of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
106
4.5 Frequency distribution of the F2 for Seed cotton yield of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
107
4.6 Frequency distribution of the F2 for boll weight of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
108
4.7 Frequency distribution of the F2 for Fibre length of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
109
4.8 Frequency distribution of the F2 for Fibre strength of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
110
4.9 Frequency distribution of the F2 for Fibre fineness of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
111
4.10 Frequency distribution of the F2 for Ginning out turn of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
112
4.11
Frequency distribution of the F2 for Relative water content of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
113
4.12 Frequency distribution of the F2 for Excised leaf water loss of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
114
4.13 Frequency distribution of the F2 for Leaf temperature of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
115
4.14 Frequency distribution of the F2 for Leaf area of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
116
4.15 Frequency distribution of the F2 for plant height of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
117
4.16 Frequency distribution of the F2 for monopodial branches of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions
118
4.17 Frequency distribution of the F2 for sympodial branches of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
119
4.18 Frequency distribution of the F2 for bolls/plant of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
120
4.19 Frequency distribution of the F2 for Seed cotton yield of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
121
4.20 Frequency distribution of the F2 for Boll weight of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
122
4.21 Frequency distribution of the F2 for Fibre length of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
123
4.22 Frequency distribution of the F2 for Fibre strength of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
124
4.23 Frequency distribution of the F2 for Fibre fineness of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
125
4.24 Frequency distribution of the F2 for Ginning out turn of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
126
4.25 Frequency distribution of the F2 for Relative water content of cross (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
127
4.26 Frequency distribution of the F2 for ELWL of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions. 128
4.27 Frequency distribution of the F2 for Leaf temperature of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
129
4.28 Frequency distribution of the F2 for Leaf area of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and (b) drought conditions.
130
LIST OF APPENDICES
Appendix Description Page
1. Comparison of Means for shoot length and root length under normal and drought
174
2. Comparison of Means for Lateral root number and lateral root density under normal and drought
175
3. List of 30 SSR primers used in study 176
4. Meteorological data recorded at University of Agriculture, Faisalabad, during the cotton crop season 2009.
177
ABSTRACT
Fifty lines of Gossypium hirsutum L. were screened at seedling stage in glasshouse for drought tolerance. From the germplasm two drought tolerant and two susceptible lines showing genetic divergence will be identified and crossed to obtain hybrid seed. The hybrid seed was planted to develop F1 generations. Some of the plants from F1 generation were selfed for F2 and some back crossed to both the parents (P1 and P2) to develop seed for back crosses (B1 and B2). All the six generations, P1, P2, F1, F2, B1 and B2 were studied in field under normal and water stressed conditions using completete block design with three replications. During the crop season, water stress will be developed by supplying 50% less irrigations than the normal. Data was recorded on different plant traits related to drought tolerance, yield and fiber quality. The inheritance pattern of various traits was studied using generation means analysis technique. Estimates of narrow sense heritability and nature of correlation among various traits was examined. There were significant differences among six generations (P1, P2, F1, F2, B1, B2) of two crosses for all the studied plant traits of crosses NIAB-78 × CIM-446 and CIM-482 × FH 1000 under both normal all drought conditions. Generation means analysis indicated additive, dominance and epistatic genetic effects played role in the inheritance of all the traits under both normal and drought condition. Two parameter model [md] provided best fit of observed to the expected generation means for number of bolls per plant under normal conditions in cross NIAB-78 × CIM-446 and for number of monopodial branches of the same cross under drought conditions. In case of cross CIM-482 × FH-1000 two parameter model [md] was found fit for Fiber fineness under normal conditions. The dominace or dominace × dominance effects were observed for some traits in both the crosses under both normal and drought conditions. Some plant traits showed [i], [j] and [l] type of interactions together which indicated complex inheritance of these traits. In the generation variance analysis only additive effects were involved in the inheritance of most studied plant traits but generation means analysis showed that additive, dominance and epistatic effects were involved in the inheritance of these traits. The narrow sense heritability estimates of infinity generation (F∞) were consistently higher than F2 generation. High narrow sense heritability estimates 0.67, 0.66 and 0.65 were observed for number of sympodial branches, number of bolls per plant and seed cotton yield, respectively for cross-1 (NIAB-78 × CIM-446) under normal conditions and narrow sense heritability estimates 0.79, 0.69 and 0.58 were observed for boll weight, seed cotton yield and relative leaf water content respectively under drought conditions for cross-1. Seed cotton yield had positive significant correlation with boll weight, fibre length, fibre strength, lint percentage and relative water content except fibre fineness, exised leaf water loss, leaf temperature and leaf area in cross-1 (NIAB-78 × CIM-446) under normal and drought conditions and in cross-2 (CIM-482 × FH-1000) under normal conditions. The information derived from these studies will provide guideline to cotton breeders in breeding of drought tolerant cotton cultivars.
1
CHAPTER 1
INTRODUCTION
Like many other developing countries, the economy of Pakistan entirely depends
upon Agriculture. Despite substantial progress made in diversified resources, Agriculture still
plays the most important role in Pakistan’s economy. It contributes 21% to GDP and
provides livelihood to 45% of the work force (Anonymous, 2009-10). Cotton commonly
known as white gold of Pakistan accounts for 8.6 % of the value addition in agriculture and
1.8% to GDP (Anonymous, 2009-10). Pakistan ranked fourth in cotton production after
Peoples Republic of China, USA and India. It is very important source of fibre and vegetable
oil in Pakistan. Linters provide cellulose for plastics and explosives. The meal and hull are
used as livestock, poultry and fish feed and its sticks are used as fuel in the villages. It is a
leading exporting commodity of Pakistan and earns a substantial amount of foreign exchange
through the export of raw cotton and its finished products, in view of its contribution, it is
rightly called the back bone of Agrarian economy of the country.
Cotton grown in Pakistan belongs to the species Gossypium hirsutum L. The genus
Gossypium is very large, containing 50 species with basic chromosome number of 13. There
are two diploid and two tetraploid species of Gossypium which have spinable seed fibers
called lint. Diploid species of Gossypium include G. herbaceum and G. arboreum with
chromosome number (2n = 2x = 26) while tetraploid species of Gossypium include G.
hirsutum and G. barbadense (2n = 4x =52). G. hirsutum which is also known as upland
cotton is the principal cultivated cotton and accounts for about 90% of the world’ cotton
production (Poehlman & Sleper, 1995). Cotton was grown over a vast area in Pakistan and
during the year 2009-10 area under cotton crop was 3.106 million hectares with a production
of 12.7 million bales (Anonymous, 2009-010).
Growth and productivity of crop plants is adversely affected by various biotic as well
as abiotic stresses such as cold, salinity, drought, heat and heavy metal toxicity. All these
stresses are a menace for crop plants and prevent them from attaining their full genetic
potential. Water stress restricts crops yields in arid and semiarid zones of the world (Jafar et
al., 2004). In Pakistan, drought is one of them which is seriously affecting whole of the
agriculture system and expected to be more and more serious with ever increasing shortage
of irrigation water in the country.
2
Drought stress is a meteorological event which comprises of the lack of rain fall for a
period of time causing moisture deficit in soil with a decrease of water potential in plant
tissues (Kramer, 1980). In agriculture its definition would be the shortage of water
availability, including rainfall and soil moisture storage ability, in amount and distribution
during the life cycle of a crop plants, which restricts, the expression of full genetic potential
of the plant (Sinha, 1986). Drought stress develops when the amount of water depleted from
the plant body is more as compared to water taken inside the plant. This stress leads to
physiological changes in plants like loss of turgor, closing of stomata, reduction in cell
enlargement and reduced leaf area. All these factors ultimately decrease photosynthesis and
respiration (Human and Toit, 1990; Hall et al., 1990).
Drought resistance mechanisms can be grouped in to three categories viz. drought
escape, drought avoidance and drought tolerance (Levitt, 1972). Drought escape is defined as
the capability of a plant to complete its life cycle before severe soil and plant water deficits
occurs and thus never faces water shortage. This mechanism involves quick phenological
development and developmental flexibility (Turner, 1979). Drought avoidance is the ability
of a plant to maintain comparatively high tissue water potential, in spite of a deficiency of
soil-moisture. Drought tolerance is the ability of a plant to survive water-deficit, with low
tissue water potential. Drought tolerance means those varieties or species of plants that are
capable to grow and yield adequately in areas which are liable to periodic drought.
The population of the world is increasing at an alarming rate and it is now
approaching 6 billion which is expected to reach 8 billion by the year 2025. Therefore, in
order to meet food and fibre needs of large number of people we need to minimize losses due
to various stresses in agricultural crops like Wheat, Cotton, Maize and rice. According to
estimation up to 45% of the world agriculture lands are subjected to continuous or frequent
drought (Bot et al., 2000).
Total area of Pakistan is 79.61 mha and out of which 4.40 mha is drought affected
(Economic Survey of Pakistan, 2000), which is a major problem in increasing production of
crops. The availability of irrigation water in Pakistan is fastly going down and down day by
day. According to Asian Water Development Outlook 2007 (report of the Asian
Development Bank) Per capita available water in Pakistan reduced from 2,961 m3 per year in
3
2000 to 1, 420 m3 per year in 2005 and just a little over 1,000 m3 per year in 2006-07,
fractionally over the scarcity threshold.
The production potential of cotton varieties in Pakistan is faced with different types of
biotic as well as abiotic stresses. Among abiotic stresses drought is the one which is not only a
serious problem that limits the cotton production in Pakistan, is also a threat to agriculture like
in many regions of the world. Saranga et al, (2001) and Le Houerou (1996) emphasized
drought as major factor of crop productivity reduction. They reported that it is expected to
increase with the spread of arid lands and global warming. However, Christiansen and Lewis
(1982) suggested to overcome the problem either by providing irrigation to the crop or by
developing varieties which can produce higher and stable yield in water limiting areas. Thus,
the development of drought tolerant cotton genotypes is a practical solution to lessen the
negative effects of drought on crop productivity.
Drought is widely considered to be the most important abiotic factor that restricts
agricultural crop production (Nemeth et al., 2002; Lea et al., 2004). As a result overall
production of crop is decreased. Cotton plant has good potential for water stress tolerance
because it has well-developed root system and ability to stand well against temporary wilting.
The yield is severely affected when drought stress occurs during reproductive stage of the crop
(Selote and chopra, 2004). Moisture stress reduces growth and photosynthesis, increases fruit
shedding and affects other physiological processes, resulting in marked decrease in cotton
yield. When drought stress occurs during fibre elongation period causes decreased fibre
length, and drought stress after fibre elongation period results in fibre immaturity and low
micronair.
Drought resistance strategies vary with climatic or soil conditions. A plant that is capable
of acquiring more water or that has higher water use efficiency will have greater resistance to
drought. Some plants possess adaptations such as C4 and CAM modes of metabolism that allow
them to exploit more arid environments. In addition, plants possess acclimation mechanism that
is activated in response to water stress (Tiaz and Zeiger, 1991).
For successful cotton breeding programme knowledge of genetic information about
physiological and agronomic traits is necessary to breed cotton for drought tolerance. The gene
action of the traits also provides information necessary in the choice of a selection strategy in
breeding cotton. Information about the correlation of the traits is necessary to obtain the
4
expected response of other traits. The information derived from these studies will provide
guideline to cotton breeders in breeding of drought tolerant cotton cultivars.
Objectives of the study
1. To investigate the genetics of physiological and agronomic traits for drought tolerance in
cotton.
2. To measure correlation among different traits studied.
5
CHAPTER 2
REVIEW OF LITERATURE
2.1 Effect of water stress on cotton and other crop plants
All physiological processes in plants depend on water which accounts for 80–95 % of
the biomass of non-woody plants (Hirt and Shinozaki, 2004). Both biotic and abiotic stresses
adversely affect plant development and cause significant reduction in yield and quality of
crops worldwide (Boyer, 1982). Seki et al. (2002) reported that moisture deficit affects plant
growth significantly if the quantity or quality of water supplied is insufficient to meet the
basic needs of plants. Drought causes significant losses in growth and productivity by
affecting morphological, physiological, biochemical and molecular processes in plants
throughout their life cycle (Farooq et al., 2009). Lee, (1984) reported that adequate soil
moisture supplied at appropriate time through artificial irrigation system or through
precipitation is essential for good crop harvest. Cotton is cultivated during summer season in
arid and semi arid areas of Pakistan and like other agricultural crops, its growth and
development is adversely affected by water stress which has adverse effect on its yield and
quality. Therefore, such varieties of cotton are needed that can either grow successfully in
drought stress conditions with very little or with out any loss in crop productivity and quality
in dry land areas or give more yield by using less quantity of water in irrigated areas.
Therefore, an understanding, of the reaction of cotton plants to moisture stress is imperative
in order to estimate irrigation needs and breed drought resistant cotton cultivars (Pace et al.,
1999).
Basically cotton is a drought tolerant crop as compared to other crops because of
various mechanisms including osmotic adjustment, very deep tap root system and choosy
fruit shedding. Response of cotton plant to moisture stress vary depending upon the severity
of stress, stage of crop growth and the length of time for which stress is imposed on the crop
(Pettigrew, 2004 ). If the stress occurs prior to bloom, it can lessen the number of fruiting
branches. Drought after bloom has maximum effect on yield of cotton and quality of lint. As
more and more bolls are produced, cotton plant’s requirement for water increase
significantly. Drought stress not only slows down plant growth, the plants also shed small
bolls and squares due to increased requirement for water. Drought amplifies the effects of
6
high temperature. Under drought stress, growth and development is badly affected due to rise
in temperature. Availability of knowledge about particular traits that determine performance
of crop under water deficit conditions, and the possibility of them either through conventional
breeding or genetic transformation approaches, could help cotton breeders to produce drought
tolerant varieties (Turner, 1997). Ball et al. (1994) studied the differential growth response of
roots and shoots to water stress and reported that root elongation of field plants was less
sensitive to drought than leaves. It was also observed that small roots were more sensitive to
drought than medium sized. Commonly tips of small roots stopped growing several days
before as compared to medium roots. Therefore it was concluded that medium roots are more
important for continuing growth in moisture stress conditions.
Mcmichal and Quisenberry (1991) reported that terminal drought decreased the
SSR (PCR) of twelve cotton genotypes with primer BNL-3383 M is a 1Kb ladder. 1.CIM-446, 2.CIM-482, 3.NIAB-78, 4.FH-1000, 5.NIAB-111, 6.CIM-1100 7.FH-900, 8.VH142, 9.CIM-707, 10.CIM-473, 11.FH-901, 12.BH-160
80
Dendrogram
81
Table. 4.3. Similarity matrix for Nei’s and Li’s coefficient of 12 cotton
Table.4.4.Generation Means of various morphological and physiological traits of Cross-1 (NIAB-78 × CIM-446) and Cross-2 (CIM-482 × FH-1000) under normal conditions.
Traits Cross (C)
Generations Pop. Effects
LSD (0.05) P1 P2 F1 F2 B1 B2
Leaf Area
C1 177.10 d 191.47 b 193.03 b 188.64 c 179.01 d 197.43 a ** 2.76
C2 174.83 c 190.63 a
193.37 a
181.34 b
178.38 b
191.51 a ** 3.19
Leaf Temp C1 29.83 b 30.66 a 30.566 29.79 b 29.63 b 30.95 a ** 0.56
C2 28.56 c
29.63 ab
29.43 ab
28.44 c
29.04 bc
30.05 a ** 0.69
ELWL C1 2.51 d 3.57 a 2.62 d 2.84 c 2.36 e 3.31 b ** 0.12
C2 2.54 d
3.54 a
2.79 c
2.80 c 2.44 e
3.38 b ** 0.08
RWC C1 88.09 a 80.20 c 88.02 a 84.14 b 87.88 a 82.01 c ** 2.02
C2 85.66 a
78.88 d
84.43 a
81.62 bc
83.86 ab
80.54 cd ** 2.65
Plant Height(cm)
C1 130.50 a 115.83 c 124.30 b 117.15 c 124.57 b 116.68 c ** 4.55
C2 126.97 a 108.63 d 124.03 a 112.57 c 117.84 b 116.22 bc
** 3.84
Monopodial Branches
C1 1.06 b 1.20 b 1.80 a 1.40 ab 1.08 b 1.13 b * 0.55
C2 1.00 c 1.66667 1.86 a 1.38 b 1.60 ab 1.67ab ** 0.36
Sympodial Branches
C1 25.33 a 21.50 b 24.90 a 20.90 b 24.47 a 21.53 b ** 1.46
C2 21.73 a 17.06 c 20.80 ab 18.09c 20.077 b 17.77 c ** 1.11
No of bolls
C1 35.03 a 30.40 c 32.13 bc 31.14 c 34.14 ab 30.85 c ** 2.26
C2 32.06 a 22.70 c 31.36 a 27.63 b 31.52 a 24.15 c ** 2.56
Boll Weight (gm)
C1 4.21 a 3.42 c 4.08 ab 3.183 4.04 ab 3.60 c ** 0.22
C2 4.05 a 3.39 c 3.91 ab 3.42 c 3.81 b 3.33 c ** 0.21
Seed Cotton Yield (gm)
C1 119.66 a 110.53 c 117.60 b 117.38 b 118.13 ab 112.09 c ** 1.90
C2 118.67 a 90.37 e 113.77 b 106.57 c 118.34 a 95.43 d ** 3.41
GOT C1 36.99 a 35.68 bc 37.50 a 36.04 b 37.44 a 35.22 c ** 0.76
C2 38.83 ab 37.59 c
39.05 a
37.10 c
38.26 b
37.07 c ** 0.64
Fibre length (mm)
C1 29.91 a 28.40 b 29.05 ab 28.59 b 28.22 b 27.84 b * 1.25
C2 28.80 a 27.24 bc 29.09 a 27.43 b 27.73 b 26.64 c ** 0.70
Fibre Strength
(g/tex)
C1 28.54 a 26.93 c 27.89 ab 27.36 bc 27.97 ab 26.73 c ** 0.79
C2 27.91 b 25.49 d 28.79 a 26.77 c 27.79 b 25.95 d ** 0.70
Fibre Fineness
(mic)
C1 3.89 d 5.01 a 3.94 d 4.22 c 4.16 c 4.80 b ** 0.17
C2 4.03 d
4.69 a
4.26 bc
4.32 b
4.07 cd
4.36 b ** 0.19
*, P < (0.05); **, P < (0.01), ns = non-significant Mean separation is by row and is based on pair wise comparison test for generations means
85
Table.4.5. Generation Means of various morphological and physiological traits of Cross-1 (NIAB-78 × CIM-446) and Cross-2 (CIM-482 × FH-1000) under drought conditions.
Traits Cross (C)
Generations Pop. Effects
LSD (0.05) P1 P2 F1 F2 B1 B2
Leaf Area
C1 158.93 e 193.63 a 187.13 b 176.66 d 161.27 e 180.68 c ** 3.36
C2 156.73 d
181.30 a 182.43 a 172.79 b
166.52 c
180.69 a ** 5.03
Leaf Temp C1 30.90 d 32.46 ab 32.53 a 31.94 c 31.78 c 31.98 bc ** 0.49
C2 31.46 b
32.76 a
30.06 c
31.49 b
31.04 bc
31.75 b ** 0.99
ELWL C1 2.04 d 3.03 a 2.18 c 2.18 c 1.85 e 2.74 b ** 0.08
C2 2.47 a
2.14 b
2.20 b
2.03 c
2.40 a
2.23 b ** 0.09
RWC C1 83.25 a 75.19 c 82.64 a 78.69 b 83.13 a 76.18 c ** 1.73
C2 81.31 a
72.55 c
80.46 a
77.15 b
80.22 a
75.92 b ** 1.66
Plant Height(cm)
C1 118.93 a 107.73 c 119.60 a 117.020 113.41 b 109.23 c ** 3.51
C2 114.47 a
87.40 d 113.27 a 104.45 b
112.17 a
95.42 c ** 3.21
Monopodial
Branches
C1 2.00 b 2.76 a 2.26 b 2.36 ab 2.00 b 2.24 b * 0.47
C2 1.40 c
2.33 a
2.46 a
2.17 ab
1.91 b
2.13 ab ** 0.42
Sympodial Branches
C1 19.06 a 16.66 b 19.93 a 17.16 b 19.16 a 17.11 b * 1.90
C2 17.50 a
14.86 b
17.57 a
16.90 a
17.57 a
16.25 a * 1.48
No of bolls
C1 26.30 a 22.06 c 21.86 c 24.04 b 25.67 a 22.31 c ** 1.25
C2 23.03 a
16.56 e
21.86 b
20.72 c
21.94 b
18.68 d ** 0.92
Boll Weight
(gm)
C1 3.68 a 3.05 bc 3.32 b 2.93 c 3.35 b 2.99 c ** 0.30
C2 3.26 a
2.54 e
2.93 c
2.75 d
3.11 b
2.48 e ** 0.13
Seed Cotton
Yield (gm)
C1 101.77 a 93.23 b 102.30 a 95.85 b 101.03 a 95.06 b ** 4.24
C2 86.60 b
66.53 d
84.86 b
82.50 c
94.744 a 68.45 d ** 2.31
GOT C1 36.05 a 35.18 c 36.20 a 35.45 bc 35.75 ab 35.25 bc ** 0.55
C2 37.27 b
36.09 e
37.88 a
36.83 cd
37.02 bc
36.46 de ** 0.44
Fibre length (mm)
C1 26.43 a 25.07 bcd 25.56 b 24.81 cd 25.17 bc 24.42 d ** 0.66
C2 25.95 a
23.83 bc
26.35 a
22.97 c
24.59 b 23.10 c ** 1.08
Fibre Strength (g/tex)
C1 24.26 a 22.26 c 23.31 b 22.45 c 24.95 a 20.84 d ** 0.76
C2 26.06 ab
20.22 d
26.61 a 23.21 c
25.30 b
21.02 d ** 0.92
Fibre Fineness
(mic)
C1 3.29 c 4.10 a 2.98 d 3.72 b 3.39 c 3.80 b ** 0.17
C2 4.36 ab
3.53 d
4.15 bc
4.04 c
4.60 a
3.98 c ** 0.27
*, P < (0.05); **, P < (0.01), ns = non-significat Mean separation is by row and is based on pair wise comparison test for generations means
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Table 4.6. Best model fit estimates for generation means parameters (± standard error) by weighted least squares analysis of various morphological and physiological traits for cross-1 (Niab-78×CIM-446) and cross-2 (CIM- 482×FH-1000) under normal conditions
Table.4.7.Best model fit estimates for generation means parameters (± standard error) by weighted least squares analysis of various morphological and physiological traits for cross-1 (Niab-78×CIM-446) and cross-2 (CIM-482×FH-1000) under drought conditions.
Under normal conditions five parameters [mdhij] in cross-1 and also five parameters model
[mdhil] in cross-2 were found fit of the observed to expected generation means (Table 4.6). In
cross-1 and 2 dominance genetic effects [h] were greater than the additive effects, which indicated
heterosis either due to overdominance or dispersion of genes in the parents. In cross-1 and 2
presence of interaction showed that inheritance of this trait was not simple. Therefore, selection in
advanced segregating generations may be useful to breed cotton for this trait.
Under drought conditions four parameters [mdhj] in cross-1 and three parameters [mdh]
model in cross-2 were found fit of the observed to the expected generation means (Table 4.7). In
cross-2 dominance genetic effects were found greater than the additive effects, which indicated
heterosis either due to overdominance or dispersion of genes in the parents. The negative
dominance effects for leaf temperature indicated that decrease was dominant over increase in cross-
2. In cross-1 presence of interaction showed that inheritance of this trait was not simple. Therefore,
selection in advanced generations may be fruitful to breed cotton for this trait. In cross-2 three
parameters model [m, d, h] was best fit indicating that inheritance of this trait was relatively simple.
Therefore, selection in early segregating generations would be useful.
4. 3.3. Excised leaf water loss (ELWL)
Models of four parameter m, d, h and j in cross-1 and m, d, i and j in cross-2 were adequate
under normal conditions for ELWL; whereas, under drought four parameter [mdij] in cross-1 and
five parameter [mdhil] models in cross-2 provided best fit of the observed to the expected
generation means For excised leaf water loss, under normal conditions, four parameter [mdhj]
model in cross-1 while in cross-2 four parameter model [mdij] provided a best fit of the observed to
the expected generation means respectively for this trait.
Both additive and nonaddditive alongwith epistatic effects were noted in the expression of
ELWL in both the crosses under both the environmental regimes. Therefore, both the crosses did
not show any promise as a breeding material for improvement of this trait through selection in early
generations.
Malik and Wright (1995) estimated additive and dominance gene action of ELWL from their
studies under drought conditions in wheat. Ahmed et al. (2000) reported that dominance along with
additive x dominance interaction controlled the inheritance of ELWL under drought conditions in
wheat. Majeed et al. (2001) observed dominance and epistatic effects in the inheritance of ELWL
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under drought conditions in barley. Kumar and Sharma (2007) applied generation means analysis to
estimate inheritance of ELWL under drought conditions in wheat and reported that additive,
dominance and epistatic effects were responsible for the inheritance of this trait.
4. 3.4 Relative water content (RWC)
For RWC, five parameters [mdhij] in cross-1 and four parameter [mdhi] models in cross-2
were fit under normal conditions. Similarly, under drought, five parameter [mdhij] in cross-1 and
four parameter [mdhi] models in cross-2 were adequate for the trait.
Although both the crosses showed their consistant behavior over the change in irrigation levels, the
genetic control of RWC Cross-1 involved non-fixable epistatic effects of the type [j] which
indicated the possibility of improvement of this trait in latter segregating generations. However,
Cross-2, which was free of non-fixable epistatic effects and involved additive type of gene action
alongwith additive × additive (fixable) epistasis for genetic controle of inheritance of RWC could
be focused upon for its improvement through selection.
Malik and Wright (1995) conducted generation means analysis to estimate inheritance of
relative water content under moisture deficit conditions in wheat and found that additive and
dominance along with additive x dominance interaction were responsible in the inheritance of this
trait. Ahmed et al. (2000) estimated additive and additive x dominance interaction for the
inheritance of RWC under drought conditions in wheat. Majeed et al. (2001) reported that only
additive type of gene action controlled the inheritance of relative water content under drought
conditions in barley. Kumar and Sharma (2007) estimated inheritance of relative water content
under drought conditions in wheat and found that additive, dominance and epistatic effects
governed the inheritance of this trait.
4. 3.5. Plant height
Under normal conditions four parameters model [mdhi] in cross-1 and five parameters
model [mdhij] in cross-2 were found fit of the observed to the expected generation means (Table
4.6). In cross-1 and 2 dominance effects [h] were greater than additive showing thereby presence of
heterosis which may either be due to overdominance or dispersion of dominant genes among the
parents. But the presence of epistatic effects particularly in cross-2 reveals ineffectiveness of
selection for improvement of plant height.
Under droughtful conditions five parameters model [mdhil] in cross-1 and four parameter
[mdjl] model in cross-2 were found adequate for plant height (Table 4.7). Both additive and non
additive gene actions along with different epistatic effects were observed to be involved in the
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inheritance of plant height under drought conditions. Opposite signs of h and l indicate that
duplicate type of gene interaction prevailed in cross-1.
The results are in accordance with Singh et al. 1983 and Randhawa et al. 1986, Mukhtar et
al. (2000a), Subhani and Chowdhry (2000), Ahuja et al. (2004), Ahmed et al. (2006), Murugan and
Ganesan (2006), Patra et al. (2006) who showed additive type of gene action for plant height trait.
However overdominance and epistatic type of gene action were reported by Singh et al. 1983,
Randhawa et al. 1986 and Saravanan et al. (2003).
4. 3.6. Number of monopodial branches
For number of monopodial branches per plant a two parameter [ml] and three parameters
models [mdh] appeared to be the best fit in cross-1 and 2 respectively under normal conditions
(Table 4.6). Greater value of h in cross-2 indicated the presence of heterosis and the inheritance of
this character was free of any epistatic effects.
Similarly, under drought, two parameter [md] in cross-1 and three parameter [mdh] model in
cross-2 indicated the best fitness of the observed to expected generation means for number of
monopodial branches (Table 4.7).
In cross-2, the situation remained unchanged with the change in irrigation levels.
Greater values of h under both the regimes indicated the presence of heterosis. Singh et al. (1971)
found additive and dominance genetic variances with the genetic interactions in the inheritance of
monopodial branches. Abro (2003) repoted that number of monopodia was governed by partial
dominance type of gene action. Abbas et al. (2008) observed Additive type of gene action along
with partial dominance for number of monopodial branches.
4. 3.7. Number of sympodial branches
Five parameter [mdhij] in cross-1 and four parameters [mdhi] models in cross-2 were best fit
for sympodial branches under normal conditions (Table 4.6).
Similarly, under droughtful conditions four parameters [mdhi] in cross-1 and three
parameter [mdh] model in cross-2 were adequate (Table 4.7) for this plant trait.
Both additive and non additive gene actions with greater dominance effects than additive
ones were operative in the inheritance of this trait. Epistatic effects were also evident except in
cross-2 under drought where h is almost equal to d. Sympodial branches in cotton plant is a
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desirable character and selection may be effective for its improvement in cross-2 under drought
conditions.
Similar results have been reported by various workers, e.g. Singh et al. (1971) they
studied the genetics of the number of sympodial branches in cotton and revealed significant
additive and dominance genetic variance along with interactions for the character. Silva and Alves
(1983) reported that for number of fruiting branches (sympodial branches) additive and dominance
as well as epistasis was involved in the inheritance. Iqball and Nadeem (2003) studied inheritance
of sympodial branches through generation mean analysis and advocates the presence of additive
gene action for number of sympodial branches. Punitha et al. (1999) observed non-additive type of
gene action for sympodial branches in cotton. Sarwar et al. (2011) found additive gene action with
partial dominance for number of sympodial branches.
4. 3.8. Number of bolls per plant
For number of bolls per plant, two parameters [md] in cross-1 and four parameters [mdjl]
model in cross-2 appeared to be adequate under normal conditions (Table 4.6).
Under drought, 5 parameters [mdhij] model in cross-1 and 3 parameter [mdh] model in
cross-2 showed best fitness of the observed to the expected generation means for the trait (Table
4.7).
Under normal conditions significant additive component in cross-1 revealed that additive
variances are pronounced for this trait and there existed a scope for its genetic improvement.
However, in cross-2 epistatic effects of the type j and l are unfixable, therefore, heterosis breeding
may be rewarding for this trait.
As far as the situation under drought conditions is concerned, both additive and non-additive
gene actions indicated their involvement in the inheritance pattern of this trait in both the crosses.
Higher value of h than d indicated the presence of heterosis for number of bolls but negative sign of
h showed the trend of heterosis towards decreasing side. Further epistatic effects were also
pronounced. However, in cross-2 higher magnitude of d than h without any complication due to
epistatic effects revealed the scope of its fixation through selection. Kalsy and Garg (1988), Ahmad
et al. (2001) and Desalegn et al. (2009) reported additive gene action for the inheritance of this trait.
However, Pathak and Singh (1970) and Esmail (2007) also studied the inheritance of number of
bolls per plant in cotton and reported additive, dominance and epistatic effects for this trait.
Similarly Singh et al. (1971) studied genetics of number of bolls per plant in cotton and found
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additive and dominance genetic variances along with the interactions for this trait. Silva and Alves
(1983) studied the gene action in cotton (G. hirsutum) and reported additive and dominance affects
for number of bolls per plant. Randhawa et al. (1986) estimated genetic effects in cotton and found
additive genetic variance as well as epistasis for number of bolls per plant. Difference of gene
action in the crosses of present study and in the studies reported by the above workers might be due
to different genetic back ground of the varieties used.
4. 3.9. Boll weight
Under normal conditions 4 parameter [mdhi] model showed its adequacy to the data set for
boll weight in both the crosses (Table 4.6). Whereas under droughtful conditions, 4 parameter
[mdhi] in cross-1 and 5 parameter [mdhij] model in cross-2 appeared adequate (Table 4.7). Both the
crosses behaved almost consistent over the stress regimes with positive values of all the parameters
involved in the inheritance of boll weight. Dominance component is there but almost of equal
magnitude in cross-1 under normal and in cross 2 under drought. Overall, both the crosses seemed
convincing to be considered as far as improvement in boll weight, an important component of yield
of seed cotton is concerned.
Different types of gene actions involved in the inheritance of boll weight in cotton have been
reported in the literature by the researchers like, Pathak and Singh (1970) reported additive and
epistatic effects for this trait Singh et al. (1971), Kaseem et al. (1984) and Kalsy and Garg (1988)
observed additive and dominance genetic variance along with the epistatic effects and Tyagi (1988)
and Esmail (2007) observed additive and dominance variance.
4. 3.10. Seed cotton yield
Under normal conditions, 5 parameter models i.e., m, d, h, i and l in cross-1 and m, d, h, i
and j in cross-2 were indicated to be adequate for seed cotton yield (Table 4.6). Whereas, under
drought, 4 parameters [mdhi] in cross-1 and 5 parameter [mdhjl) model in cross-2 provided the best
fit for this trait (Table 4.7). Although additive component is greater than dominance under normal
condition in cross-1, but the presence of epistatic effects like dominance × dominance [l]
complicated the situation. Opposite signs of h and l indicated the presence of duplicated type of
gene interaction. Similarly, in cross-2, d and i are there with h almost equal to d indicating the
possibility of improving the trait through selection as well as use of heterosis breeding but in later
generations because of the presence of the epistatic effects due to additive × dominance interaction.
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Under drought (in cross-1) both additive and dominance effects were present the genes
showing non-additive influence appeared to be more important than the additive genes. The additive
× additive [i] interaction, however, indicated that fixation of additive alleles is possible in the later
segregating generations as suggested by Singh and Narayanan (2000).
In cross-2, again additive × non-additive gene actions with epistatic effects were operative for the
expression of yield of seed cotton. Greater h than d and presence of j and l indicated the unfixability
of the character and therefore, hetrosis breeding may be rewarding in this case. Opposite signs of h
and l indicated the presence of duplicated type of epistasis. The results are in agreement with Pathak
and Singh (1970), Kaseem et al. (1984), Kalsy and Garg (1988) and Esmail (2007) who studied the
inheritance of seed cotton yield per plant in cotton and reported additive, dominance and epistatic
gene effects for this trait. Similarly Randhawa et al. (1986) reported the presence of additive and
epistatic effects in the inheritance of this trait.
4. 3.11. Ginning out-turn (GOT)
Under normal irrigation regime five parameter [mdhij] models gave the best fitness in both
the crosses. Similarly, three parameter [mdl] models provided good fit for ginning out turn
percentage in both the crosses under drought conditions.
Both additive and nonadditive genes alongwith their epistatic effects were evident to be
involved in the inheritance of this trait under normal conditions in both the crosses. Greater values
of h than those of d indicated the presence of heterosis. Positive signs showed the effect of
favourable or increasing alleles for GOT but the presence of non-additive genetic and epistatic
effects do not favour the effectiveness of selection. However, heterosis breeding may be exploited.
Under droughtful regime both the crosses again showed the same genetic picture. Three
parameter (mdl) model was fit in both the crosses. Additive component was there but complicated
by epistatic effects due to dominance × dominance.
Additive, dominance and interactions were reported to be responsible for the inheritance of
lint percentage by Dhillon and Singh (1980), Singh and Yadavendra (2002) and Mert et al. (2003)
while analyzing generation means in cotton. However Pavasia et al. (1999) reported additive type of
gene action in the inheritance of lint percentage in cotton.
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4. 3.12. Fibre Length
Under no stress of water five parameter [mdhil] in cross 1 and 4 parameter [mdhl] model in
cross 2 were found best fit of the observed to the expected generation means for staple length (Table
4.6). Whereas, under drought condition 4 parameter [mdhl] in cross 1 and 4 parameter [mdil] model
in cross 2 was fit (Table 4.7).
Both additive and non-additive genes were acting and interacting in the inheritance of staple
length in both crosses under both the environmental regimes. Further, the dominance component
with reducing genes was more prominent. Staple length is one of important fibre property traits and
reduction in its expression is not a desirable characteristics, both the crosses, therefore did not
represent a suitable genetic material as for as improvement in this trait is concerned.
Singh et al. (1983) and Lin and Zhao (1988) studied gene action in cotton for this trait and
recorded additive, dominance and epistatic effects. Nadarajan and Rangasamy (1990) found that the
trait was controlled by simple additive gene action, while Singh and Yadavendra (2002) concluded
that fibre length in cotton was governed by additive and dominance genetic effects along with
involvement of interactions. Nimbalkar et al. (2004) observed in desi cotton (Gossypium arboreum
and Gossypium herbaceum) that only additive type of gene action was responsible for the
inheritance of fibre length. Murtaza et al. (2004) estimated gene action in cotton and found that
epistatic effects were responsible for the inheritance of fibre length.
4. 3.13. Fibre Strength
Four parameters, m, d, h and i model in cross-1 and m,d, j and l in cross-2 provided the best
fitness of the observed to the expected generation means for fibre strength under normal conditions
(Table 4.6). Similarly, five parameters, m, d, h, i and j model in cross-1 and m,d,h, j and l in cross-2
was adequare under drought experiment (Table 4.7). Fibre strength is another desirable and
important trait of cotton. Both additive and nonadditive components alongwith epistatic effects were
observed to be involved in the inheritance of this trait in both the crosses under both the
environments except the cross-1 which seemed a promising material as for the possibility of
improving this trait under normal conditions. In this cross prominence of d and i components are
fixable.
Pathak (1975) and Hendawy et al. (1999) observed that fibre strength in cotton had additive
and dominance genetic effects as well as additive x additive interaction. Singh et al. (1983) as well
as Lin and Zhao (1988) concluded that additive, dominance and epistatic genetic variances were
95
involved in the inheritance of fibre strength in cotton. Murtaza et al. (2004) observed that fibre
strength in cotton was controlled by additive and dominance genetic effects.
4. 3.14. Fibre Fineness
In the case of fibre fineness five parameters [mdhil] in cross-1 and two parameters [md]
model in cross-2 two were adequate under normal conditions; whereas, under drought conditions
four parameters [mdhi] in cross-1 and three parameters [mdh] model in cross-2 were found fit for
this trait. Measuring units of fibre fineness in cotton are the micronairs which means “ rate of air
flow through fibre mass”. In other words higher the micronair value coarser is the fibre and the vice
versa.The breeder therefore have to be careful during the process of selection from the breeding
material for fineness.
In the present studies both the crosses indicated significant negative values of additive
effects indicating thereby desirable situation for the improvement of fibre fineness under normal
conditions but only in cross-2 because cross-1 showed the presence of non additive and epistatic
effects in the expression of this character. Under drought conditions negative values of h, d and i in
cross-1 indicated the dominance of decreasing genes and thus seemed promising material as far as
the improvement of fibre fineness is concerned for drought tolerance. Cross-2, under drought
conditions, however proved reverse as far as the improvement of fibre fineness is concerned. Both
additive and non additive genetic effects in the phenotypic manifestation of fibre fineness have been
reported in the literature. Gad et al. (1974) estimated that additive and dominance variances were
involved in the inheritance of fibre fineness. Ma et al. (1983) evaluated six generations of cotton for
the inheritance of fibre fineness and found dominance effects for this trait. Lin and Zhao (1988)
reported from their studies in cotton that fibre fineness was governed by additive, dominance and
epistatic genetic effects. Nadarajan and Rangasamy (1990) found that fibre fineness was controlled
by additive gene action in cotton.
4.4. Generation Variance analysis
Differences in morphological and physiological traits are due to genetic and environmental
variation. Generation variance analysis has widely been used by plant breeders for partitioning the
total variance into genetic and environmental components. The partitioning of phenotypic variance
into its genotypic and environmental components is not sufficient to study the genetic properties of
a breeding material, so genotypic variance is further partitioned into additive (D), dominance (H)
and interaction (F). Genetic and environmental variance can be measured from an experiment which
96
includes some non segregating (e.g. pure lines, inbred lines, F1 etc.) and segregating populations
(e.g. backcrosses, F2 etc.). In the present studies a model incorporating DE (additive and
environmental) components gave the best fit for all the traits in both the crosses, both under normal
and drought conditions except for number of sympodial branches in cross-1 under normal
conditions where model DFE gave the best fit (Table 4.8).
97
Table.4.8 Components of variance, D (additive), F(additive× dominance), E(environmental), narrow sense heritability and genetic advance estimates of various morphological and physiological traits in cross-1 (Niab-78×CIM-446) and cross-2 (CIM- 482×FH-1000) under normal conditions.
Table 4.9. Components of variance, D (additive), F(additive× dominance), E(environmental), narrow sense heritability and genetic advance estimates of various morphological and physiological traits in cross-1 (Niab-78×CIM-446) and cross-2 (CIM-482×FH-1000) under drought conditions.
Additive and dominance genetic variance of various traits in cotton has been reported by
Gad et al. (1974), Tyagi (1988), May and Green (1994), Nistor and Nistor (1999),
Mukhtar et al. (2000), Bertini et al. (2001), Khan et al. (2001).
Both generation means and generation variance analyses indicated presence of
additive and dominance variance for various traits, but epistatic effects were not detected
in the generation variance analysis. This discrepancy may be due to differences in the
estimation precision of the two analyses. However Malik et al (1999) reported that
generation means analysis is relatively more reliable compared to generation variance
analysis. The results of generation variance analysis and narrow sense heritability (F2)
and F (infinity) and genetic advance are given in Table 4.7 and 4.8.
4.5. Heritability and genetic advance for various plant traits
The narrow sense heritability estimates for all the plant traits in F2 generation of
cross-1(NAIB 78×CM446 ) ranged between 0.67 to 0.37 under normal and 0.79 to 0.41
under drought conditions.. Johnson et. al. (1955a), categorized the heritability values as
low (less than 30 %), moderate (30-60 %) and high (more than 60 %). High narrow sense
heritability estimates 0.67, 0.66 and 0.65 were observed for number of sympodial
branches, number of bolls per plant and seed cotton yield, respectively under normal
conditions and 0.79, 0.69 and 0.58 for boll weight, seed cotton yield and relative leaf
water content respectively under drought conditions in cross-1. These high heritability
estimates were due to additive gene effects which suggested that these traits can be
improved by selection during successive generations.
The narrow sense heritability estimates of infinity generation (F∞) were
consistently higher than in F2 generation and ranged between 0.85 to 0.58 under normal
and 0.91 to 0.63 under drought conditions in the cross-1. In the cross-2, narrow sense
heritability estimates in F2 generation ranged from 0.69 to 0.17 under normal and 0.79 to
0.16 under drought conditions. In this cross high heritability estimates 0.69, 0.66 and 0.64
were observed for plant height, boll weight and number of bolls per plant respectively
under normal and 0.79, 0.76 and 0.72 for seed cotton yield , bolls per plant and boll
weight respectively under drought conditions. High heritability estimates suggested the
possibility of genetic improvement for these traits through selection in segregating
100
populations. For F infinity generation heritability estimates were ranging between 0.89 to
0.45 under normal and 0.91 to 0.51 under drought conditions in the cross-2.
Based upon the estimates of narrow sense heritability, the extent of genetic
advance for all the characters was calculated in both the crosses under normal (4.8) as
well as drought (4.9) conditions.
Under normal conditions, cross-1 revealed higher value (9.90) of genetic advance
for leaf area and moderate for plant height (5.92 ) and seed cotton yield (4.94). Whereas,
the estimates remained lesser ranging from 0.37 to 4.48 for all other traits.
Similarly, cross-2, under normal conditions indicated higher estimates of genetic
advance for plant height (9.82), leaf area (9.75) and seed cotton yield (9.27) and other
traits remained with in the range of 0.14 to 5.44 ( Table 4.8).
` Under drought, cross-1 revealed higher genetic advance (15.52) for leaf area,
moderate (6.62) for plant height and lower for other traits which remained within the
range of 0.29 and 5.62.
Similarly, the cross-2, showed higher values of seed cotton yield (17.88), plant
height (13.90) and leaf area (10.77) whereas, all other traits remained with in the range of
0.12 and 3.82 (Table 4.9). Moderate to high narrow sense heritability and genetic
advance for various plant traits inculuding plant height, seed cotton yield, number of
bolls, lint percentage, fibre length, leaf area, monopodial branches and boll weight by
Ahmed et al.(2006), Baloch et al. (2004), Kumari and Chamundeswari (2005), Singh and
Singh (1981), Gupta (1987), Ulloa (2006). However, low estimates of narrow sense
heritability for different plant traits have been observed by Murtaza (2005) and Esmail
(2007).
In the present studies the breeding material analysed genetically consisted of two
crosses. The cross NIAB-78 x CIM-446 was cross-1 and CIM-482 x FH-1000 was cross-
2. Both the crosses were studied under normal as well as drought conditions. Our main
focus was to look for the possibility of improvement of future cotton varities studied
under droughtfull conditions.The materials were suitable for the plant traits including
physiological, agronomical as well as fibre quality traits. Generation means analysis
revealed the involvement of both additive and non additive gene actions alongwith some
epistatic effects in the phenotypic manifestation of the trait.
101
Similarly, the narrow sense heritability and genetic advance estimates ranged
from low to high for the traits in both the crosses. Overall, the cross-1 proved to be
promising for improvement in the plant traits like, monopodial and sympodial branches,
boll weight, seed cotton yield and fibre fineness. In all theses traits additive type of gene
action was predominantly involed in their interitance and narrow sense heritability
estimates were high.
Similarly, cross-2 indicated to be a promising breeding material for the
improvement of leaf area, leaf temperature, relative water content, monopodia, sympodia,
number of bolls and fibre fineness because additive type of gene action was prominantly
involved in their inheritance and the heritability estimates were generally moderate.
Although the extent of genetic advance was generally low in all the traits
however, selection may yield improvement with slow progress but one has to be careful
while making selection, particularly, for the trait like, leaf area, leaf temperature, excised
leaf water loss and fibre fineness where lower or negative values will be desireable. At
the same time one has to keep an eye on the association of these plant traits with others
during the process of selection. The results of correlation studies are presented in table
4.10 to 4.13.
4.6 . Frequency distribution of F2 population
The frequency distribution, of physiological, agronomic and fibre quality traits in
F2 populations are given in Figures 4.1 to 4.28. The graphs for all the traits for crosses
NAIB-78×CIM-446 and CIM 482 ×FH 1000 under both normal and drought conditions
show near normal distribution in F2. The appearance of transgressive segregants in F2
generation is the function of the following favourable genetic situations associated with
the parents involved:
1. The character must be polygenically controlled.
2. The parents should be completely homozygous.
3. Parents should be complementary to each other for the (+v) and (-V) genes
conditioning the trait in point.
4. There should be no linkage.
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The distribution showed continuous variation representing the polygenic nature of these
traits. In all the traits some F2 plants excelled their parents exhibiting transgressive
segregation.
In case of cross-1 (NAIB 78×CM446) under normal conditions Figures 4.1- 4.14a
F1 means fall outside the parental range for leaf area, monopodial branches and lint %
age, while the remaining plant traits like, leaf temperature, excised leaf water loss,
relative water content, plant height, sympodial branches, number of bolls per plant, boll
weight, seed cotton yield, fibre length, fibre strength and fibre fineness fell inside the
parental range.
In cross-1 (NAIB-78×CIM-446) under drought conditions Figures 4.1- 4.14b F1
means were found outside the parental range for leaf temperature, plant height, sympodial
branches, seed cotton yield, lint percentage, and fibre fineness whereas the other
indicated plant traits fell inside the parental range.
In case of cross-2 (CIM 482×FH-1000) under normal conditions Figures 4.15-
4.28a F1 means fall outside the parental range and showed heterosis for monopodial
branches, lint % age, leaf area, fibre length, fibre strength, while F1 means for remaining
plant traits fell inside the parental range.
In case of cross CIM 482 ×FH 1000 under drought conditions Figures 4.15-4.28b
the heterosis was greatly pronounced for monopodial branches, sympodial branches, fibre
length, fibre strength, lint percentage leaf temperature and leaf area, whereas other plant
traits fell inside the parental range.
103
CROSS-1
(a) Normal
BC2
BC1
F2
F1
P2
P1
0
5
10
15
20
25
30
35
40
45
50
98 102 106 110 114 118 122 126 130 134
Nu
mb
er o
f p
lan
ts
Plant Height (cm)
(b) Drought
P1
P2
F1
F2
B1
B2
0
5
10
15
20
25
30
35
96 99 102 105 108 111 114 117 120 123 126 129 132
Nu
mb
er o
f p
lan
ts
Plant Height (cm)
Fig-4.1. Frequency distribution of the F2 for plant height of cross-1 (NIAB-78×CIM-446) of Cotton under ( a ) normal and ( b ) drought conditions.
104
(a) Normal
B2
B1
F2
F1
P2
P1
10
20
30
40
50
60
-1 0 1 2 3 4 5
Nu
mb
er o
f p
lan
ts
(b) Drought
P1
P2
F1F2
B1B2
10
20
30
40
50
60
-1 0 1 2 3 4 5 6 7
Nu
mb
er o
f p
lan
ts
Monopodial branches Fig-4.2. Frequency distribution of the F2 for monopodial branches of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions
105
(a) Normal
B2
B1
F2
F1
P2
P1
0
5
10
15
20
25
30
35
40
45
50
12 14 16 18 20 22 24 26 28 30
Nu
mb
er o
f p
lan
ts
Sympodial branches
(b) Drought
P1
P2
F1
F2
B1
B2
0
5
10
15
20
25
30
35
40
45
8 10 12 14 16 18 20 22 24 26
Nu
mb
er o
f p
lan
ts
Sympodial branches Fig-4.3. Frequency distribution of the F2 for sympodial branches of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
106
(a) Normal
P1
P2F1F2
B1
B2
0
5
10
15
20
25
18 20 22 24 26 28 30 32 34 36 38 40 42 44 46
Nu
mb
er o
f p
lan
ts
Drought
P1
P2
F1
B1
B2
0
5
10
15
20
25
30
35
40
45
50
16 18 20 22 24 26 28 30 32
Nu
mb
er o
f p
lan
ts
Number of bolls
Fig-4.4. Frequency distribution of the F2 for Bolls/plant of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
107
(a) Normal
B2
B1
F2
F1
P2
P1
0
5
10
15
20
25
30
35
40
45
50
96 100 104 108 112 116 120 124 128 132 136
Nu
mb
er o
f p
lan
ts
Seed cotton yield
(b) Drought
P1
P2
F1
F2B1
B2
0
5
10
15
20
25
30
35
40
45
70 75 80 85 90 95 100 105 110 115 120
Nu
mb
er
of
pla
nts
Seed cotton yield
Fig-4.5. Frequency distribution of the F2 for Seed cotton yield of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
108
(a) Normal
B2
B1F2 F1
P2
P1
0
5
10
15
20
25
30
35
40
45
2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5
Nu
mb
er o
f p
lan
ts
Boll weight
(b) Drought
P1
P2
F1
F2
B1
B2
0
5
10
15
20
25
30
1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2
Nu
mb
er o
f p
lan
ts
Boll weight
Fig-4.6. Frequency distribution of the F2 for boll weight of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
Fibre length Fig-.4.7. Frequency distribution of the F2 for Fibre length of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and (b) drought conditions.
110
(a) Normal
B2
B1F2 F1
P2
P1
0
5
10
15
20
25
30
35
40
22 23 24 25 26 27 28 29 30 31 32
Nu
mb
er o
f p
lan
ts
Fibre strength
(b) Drought
P1
P2
F1
F2
B1
B2
0
5
10
15
20
25
30
35
40
45
18 19 20 21 22 23 24 25 26 27 28
Nu
mb
er o
f p
lan
ts
Fibre strength
Fig-4.8. Frequency distribution of the F2 for Fibre strength of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
111
(a) Normal
B2
B1F2
F1
P2
P1
0
5
10
15
20
25
30
35
40
3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5 5.2 5.4
Nu
mb
er o
f p
lan
ts
Fibre fineness
(b) Drought
P1
P2
F1
F2
B1
B2
0
5
10
15
20
25
30
35
40
45
2.4 2.7 3 3.3 3.6 3.9 4.2 4.5 4.8 5.1
Nu
mb
er o
f p
lan
ts
Fibre fineness Fig-4.9. Frequency distribution of the F2 for Fibre fineness of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
112
(a) Normal
B2
B1F2
F1
P2
P1
0
5
10
15
20
25
30
35
40
45
32 33 34 35 36 37 38 39 40 41
Nu
mb
er o
f p
lan
ts
Ginning out-turn
(b) Drought
P1
P2
F1
F2 B1B2
0
5
10
15
20
25
30
32 33 34 35 36 37 38 39
Nu
mb
er o
f p
lan
ts
Ginning out-turn
Fig-4.10. Frequency distribution of the F2 for Ginning out-turn of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
113
(a) Normal
B2
B1
F2
F1P2
P1
0
5
10
15
20
25
30
35
40
74 76 78 80 82 84 86 88 90 92
Nu
mb
er o
f p
lan
ts
Relative water content
(b) Drought
P1
P2
F1
F2 B1
B2
0
5
10
15
20
25
30
35
40
45
50
68 70 72 74 76 78 80 82 84 86 88
Nu
mb
er o
f p
lan
ts
Relative water content Fig-4.11. Frequency distribution of the F2 for Relative water content of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
114
(a) Normal
B2
B1
F2F1
P2
P1
0
5
10
15
20
25
30
35
40
1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8
Nu
mb
er o
f p
lan
ts
Excised leaf water loss
(b) Drought
P1
P2
F1F2
B1 B2
0
10
20
30
40
50
60
1.4 1.8 2.2 2.6 3 3.4
Nu
mb
er o
f p
lan
ts
Excised leaf water loss Fig-4.12. Frequency distribution of the F2 for Excised leaf water loss of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
115
(a) Normal
B2
B1F2
F1P2
P1
0
10
20
30
40
50
60
25 26 27 28 29 30 31 32 33 34
Nu
mb
er o
f p
lan
ts
Leaf temperature
(b) Drought
P1
P2F1F2
B1B2
0
5
10
15
20
25
30
35
40
45
50
27 29 31 33 35 37
Nu
mb
er o
f p
lan
ts
Leaf temperature Fig-4.13. Frequency distribution of the F2 for Leaf temperature of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
116
(a) Normal
B2
B1
F2
F1
P2
P1
0
5
10
15
20
25
30
35
40
165 170 175 180 185 190 195 200 205 210
Nu
mb
er o
f p
lan
ts
Leaf area
(b) Drought
P1 P2
F1
F2
B1
B2
0
5
10
15
20
25
30
35
155 165 175 185 195 205
Nu
mb
er o
f p
lan
ts
Leaf area
Fig-4.14. Frequency distribution of the F2 for Leaf area of cross-1 (NIAB-78×CIM-446) of Cotton under (a) normal and ( b ) drought conditions.
Plant height Fig-4.15 Frequency distribution of the F2 for plant height of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
118
(a) Normal
P1
P2
F1
F2
BC1
BC2
10
20
30
40
50
60
70
-1 0 1 2 3 4 5
Nu
mb
er o
f p
lan
ts
Monopodial branches
(b) Drought
P1
P2
F1F2
BC1BC2
10
20
30
40
50
60
-1 0 1 2 3 4 5 6
Nu
mb
er o
f p
lan
ts
Monopodial branches
Fig-4.16. Frequency distribution of the F2 for monopodial branches of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
119
(a) Normal BC2
BC1
F2
F1
P2
P1
0
5
10
15
20
25
30
35
40
45
8 10 12 14 16 18 20 22 24 26 28 30
Nu
mb
er
of
pla
nts
Sympodial branches
(b) Drought
P1
P2
F1F2
BC1
BC2
0
5
10
15
20
25
30
35
40
8 10 12 14 16 18 20 22 24 26 28
Nu
mb
er o
f p
lan
ts
Sympodial branches
Fig-4.17. Frequency distribution of the F2 for sympodial branches of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
120
(a) Normal
BC2 BC1
F2
F1
P2
P1
0
5
10
15
20
25
30
16 18 20 22 24 26 28 30 32 34 36 38 40
Nu
mb
er o
f p
lan
ts
Bolls/plant
(b) Drought
P1
P2
F1
F2
BC1
BC2
0
5
10
15
20
25
30
35
8 10 12 14 16 18 20 22 24 26 28 30 32 34
Nu
mb
er
of
pla
nts
Bolls/plant
Fig-4.18. Frequency distribution of the F2 for bolls/plant of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
121
(a) Normal
BC2
BC1
F2
F1
P2
P1
0
5
10
15
20
25
30
35
40
45
85 90 95 100 105 110 115 120 125 130
Nu
mb
er o
f p
lan
ts
Seed cotton yield
(b) Drought
P1
F1F2
BC1
BC2
0
5
10
15
20
25
30
35
40
67 70 73 76 79 82 85 88 91 94 97 100
Nu
mb
er o
f p
lan
ts
Seed cotton yield Fig-4.19. Frequency distribution of the F2 for Seed cotton yield of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
122
(a) Normal
BC2
BC1F2F1
P2
P1
0
5
10
15
20
25
30
35
1.6 2 2.4 2.8 3.2 3.6 4 4.4 4.8 5.2
Nu
mb
er o
f p
lan
ts
Boll weight
(b) Drought
P1
P2
F1
F2
BC1
BC2
0
5
10
15
20
25
30
1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4
Nu
mb
er o
f p
lan
ts
Boll weight
Fig-4.20. Frequency distribution of the F2 for Boll weight of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
123
(a) Normal
P1
P2F1
F2 BC1
BC2
0
5
10
15
20
25
24 25 26 27 28 29 30 31
Nu
mb
er o
f p
lan
ts
Fibre length
(b) Drought
P1
P2
F1
F2
BC1
BC2
0
5
10
15
20
25
30
35
40
18 19 20 21 22 23 24 25 26 27 28
Nu
mb
er o
f p
lan
ts
Fibre length
Fig-4.21. Frequency distribution of the F2 for Fibre length of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
124
(a) Normal
BC2
BC1
F2
F1
P2P1
0
5
10
15
20
25
30
35
40
21 22 23 24 25 26 27 28 29 30 31 32
Nu
mb
er o
f p
lan
ts
Fibre strength
(b) Drought
P1
P2
F1
F2
BC1
BC2
0
5
10
15
20
25
30
35
19 20 21 22 23 24 25 26 27 28 29 30
Nu
mb
er o
f p
lan
ts
Fibre strength
Fig-4.22.Frequency distribution of the F2 for Fibre strength of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
Fig-4.24. Frequency distribution of the F2 for Ginning out turn of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
127
(a) Normal
BC2
BC1
F2
F1
P2
P1
0
5
10
15
20
25
30
35
40
70 72 74 76 78 80 82 84 86 88 90 92
Nu
mb
er o
f p
lan
ts
Relative water content
(b) Drought
P1
P2
F1
F2
BC1
BC2
0
5
10
15
20
25
30
35
40
45
68 70 72 74 76 78 80 82 84 86 88
Nu
mb
er o
f p
lan
ts
Relative water content
Fig-4.25. Frequency distribution of the F2 for Relative water content of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b) drought conditions.
128
(a) Normal
BC2
BC1
F2F1
P2
P1
0
10
20
30
40
50
60
2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8
Nu
mb
er o
f p
lan
ts
(b) Drought
P1
P2F1
F2
BC1
BC2
0
10
20
30
40
50
60
70
80
1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8
Nu
mb
er o
f p
lan
ts
Excised Leaf Water Loss
Fig-4.26. Frequency distribution of the F2 for ELWL of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
129
(a) Normal
BC2BC1
F2F1
P2P1
0
5
10
15
20
25
30
35
40
24 25 26 27 28 29 30 31 32
Nu
mb
er o
f p
lan
ts
(b) Drought
P1
P2
F1
F2
BC1BC2
0
5
10
15
20
25
30
35
40
27 28 29 30 31 32 33 34 35 36
Nu
mb
er
of
pla
nts
Leaf temperature
Fig-4.27. Frequency distribution of the F2 for Leaf temperature of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
130
(a) Normal
BC2
BC1 F2
F1P2
P1
0
5
10
15
20
25
30
35
40
164 168 172 176 180 184 188 192 196 200 204
Nu
mb
er o
f p
lan
ts
(b) Drought
P1
P2F1
F2
BC1
BC2
0
5
10
15
20
25
30
35
40
45
50
152 156 160 164 168 172 176 180 184 188 192 196
Nu
mb
er o
f p
lan
ts
Leaf area
Fig-4.28. Frequency distribution of the F2 for Leaf area of cross-2 (CIM-482×FH-1000) of Cotton under (a) normal and ( b ) drought conditions.
131
4.7. Correlation studies
Correlation is degree of association among the traits. To breed a high yielding
cultivar, breeder has to tailor a plant with combination of a number of desirable traits.
The estimates of correlation among traits are helpful for planning a breeding programme
to synthesize a genotype with desirable traits. Correlation was estimated among
agronomic and the traits related to drought resistance in cotton. Four large F2 populations
(150 plants from each population) involving parents with contrasting traits were used in
correlation studies. The correlation calculated in such a recombinant large population
shows linkage behavior of the genes (Malik et al. 2006). Generally, the correlations for
the pair of traits among the populations were consistent. However, in some cases
correlation was significant for a trait in one cross but non-significant in the other. This
may be due to the difference in allele combinations of the parents involved in the
populations. Correlation matrix among the traits in both the crosses is given in
Table 4.10-4.13.
4.7.1 Plant height
Plant height was positively and significantly correlated with sympodial branches,
number of bolls per plant, seed cotton yield, boll weight, fibre length, fibre strength, lint
percentage and relative water content and it had negative non significant correlation with
monopodial branches, excised leaf water loss, leaf temperature and leaf area in cross-1
under normal and drought conditions and in cross-2 under normal conditions. In cross-2
under drought conditions, plant height indicated negative but non significant correlation
with monopodial branches, leaf temperature and leaf area. Whereas, significant and
positive correlation with all others.
132
Table.4.10. Genotypic (upper value) and phenotypic (lower value) correlations for different plant traits in cross-1 (NIAB-78 x CIM 446) of cotton under normal conditions. Traits Mono Symp BN SCY BW FL FS FF GOT RWC ELWL LT LA
BW G 0.79* 0.97* -0.98 0.90* 0.97* -0.99 -0.73 -0.69 P 0.69** 0.93** -0.99** 0.85** 0.98** -0.96 -0.66** -0.67**
FL G 0.98* -0.79 0.62* 0.64* -0.54 -0.51 -0.63 P 0.81** -0.70** 0.54* 0.60** -0.49* -0.39 -0.56*
FS G -0.96 0.93* 0.99* -0.95 -0.77 -0.87 P -0.90** 0.86** 0.92** -0.88** -0.69** -0.82**
FF G -0.88 -0.97 0.95 0.68* 0.60* P -0.84** -0.95** 0.93** 0.65** 0.59*
GOT G 0.99* -0.91 -0.65 -0.64 P 0.93** -0.88** -0.56* -0.62**
RLWC G -0.99 -0.66 -0.65 P -0.97** -0.61** -0.64**
ELWL G 0.81* 0.72* P 0.76* 0.71**
LT G 0.93* P 0.87**
* = P < 0.05, ** = P < 0.01 Plant traits: Plant Height (PH, cm), Monopodial Branches, Sympodial Branches, Boll Number (BN),Seed Cotton Yield (SCY, g), Boll Weight (BW, g), Fibre Length (FL, mm), Fibre Strength (FS, g/tex), Fibre Fineness (FF. Mic), Lint Percentage (LP, %), Relative Water Content (RWC, %), Excised Leaf Water Loss (ELWL, g/g), Leaf Temperature(LT) and Leaf area (LA)
133
Table. 4.11. Genotypic (upper value) and phenotypic (lower value) correlations for for different plant traits in cross-2 (CIM 482x FH-1000) of cotton under normal conditions. Traits Mono Symp BN SCY BW FL FS FF GOT RWC ELWL LT LA
BW G 0.92* 0.92* -0.82 0.99* 0.99* -0.82 -0.48 -0.48 P 0.91** 0.89** -0.77** 0.95** 0.95** -0.79** -0.45 -0.47*
FL G 0.93* -0.58 0.97* 0.94* -0.66 -0.43 -0.23 P 0.89** -0.54* 0.94** 0.84** -0.64** -0.43 -0.22
FS G -0.80 0.90* 0.97* -0.84 -0.44 -0.29 P -0.77** 0.86** 0.93** -0.83** -0.42 -0.28
FF G -0.59 -0.99 0.94* 0.63 0.73* P -0.55* -0.91** 0.91* 0.54* 0.69**
GOT G 0.93* 0.62 -0.22 -0.22 P 0.82** -0.60** -0.23 -0.19
RLWC G -0.93 -0.62 -0.57 P -0.89** -0.53* -0.55
ELWL G 0.79* 0.74* P 0.73** 0.73** G 0.89*
* = P < 0.05, ** = P < 0.01 Plant traits: Plant Height (PH, cm), Monopodial Branches, Sympodial Branches, Boll Number (BN),Seed Cotton Yield (SCY, g), Boll Weight (BW, g), Fibre Length (FL, mm), Fibre Strength (FS, g/tex), Fibre Fineness (FF. Mic), Lint Percentage (LP, %), Relative Water Content (RWC, %), Excised Leaf Water Loss (ELWL, g/g), Leaf Temperature(LT) and Leaf area (LA)
134
Table. 4.12. Genotypic (upper value) and phenotypic (lower value) correlations for different plant traits in cross-1 (NIAB-78 x CIM 446) of cotton under drought conditions. Traits Mono Symp BN SCY BW FL FS FF GOT RWC ELWL LT LA
showed that low rate of water loss from leaves would maintain higher relative water content in
plants under drought stress and hence would improve the agronomic traits. Positive correlation of
relative water content with plant height, seed cotton yield, boll number, boll weight, lint
percentage, fibre length, fibre strength and fibre fineness indicated the same. Leaf temperature
had significant and positive correlation with leaf area. Malik et al. (2006) reported that relative
water content showed positive correlation with boll weight and negative with fibre length, while it
had no correlation with other agronomic traits. They also observed that excised leaf water loss
indicated no correlation with any of the agronomic traits. Absence of correlation between traits
indicated that those traits segregate independently at the time of gamete formation. So those traits
might be selected with desired combination of characters during segregating generations. In the
present study negative correlation of excised leaf water loss with relative water content revealed
that the genes which restrict water loss of leaves may help to maintain higher relative water
content.
143
CHAPTER-5
SUMMARY
Four cotton genopypes were selected on the basis of seedling traits and SSR analysis and
their six generations ((P1, P2, F1, F2, BC1, BC2) were evaluated in triplicated randomized
complete block design under both normal and drought conditions in the field. The mean of each
cross combination was analysed separately to estimate standard error (S.E) of means, and
narrow-sense heritability for F2 and F infinity (F∞) generation for various palnt characters. The
nature and magnitude of genetic effects involved in the expression of these characters was
determined. The degree and direction of association between morphological and physiological
traits was also determined in the F2 generation of each cross under both normal and droughtful
conditions.
There were significant differences among six generations (P1, P2, F1, F2, BC1, BC2) of
two crosses for all the studied plant traits of crosses NIAB-78 × CIM-446 and CIM-482 × FH
1000 under both normal all drought conditions. The F1 means for sympodial branches, boll
weight, seed cotton yield and relative water contents of cross (NIAB-78 × CIM-446) under
normal conditions were similar to the high parent means showing complete dominance and plant
height under normal and droght and relative water contenets under normal condition in cross
(CIM-482 × FH-1000) were also similar to the high parent means showing complete dominance.
Generation means analysis indicated additive, dominance and epistatic genetic effects
played role in the inheritance of all the traits under both normal and drought condition. Two
parameter model [md] provided best fit of observed to the expected generation means for number
of bolls per plant under normal conditions in cross NIAB-78 × CIM-446 and for number of
monopodial branches of the same cross under drought conditions. In case of cross CIM-482 ×
FH-1000 two parameter model [md] was found fit for Fiber fineness under normal conditions.
Leaf temperature, number of bolls per plant fibre fineness, monopodial branches,
sympodial branches in cross 2 (CIM-482 × FH-1000) under normal condtions and monopodial
and sympodial branches of the same cross under drought condtions exhibited simple inheritance
with additive dominance model. The remaining plant traits showed higher parameter model and
exhibited complex inheritance in both crosses under both environments. The dominace or
dominace × dominance effects were observed for some traits in both the corosses under both
144
normal and drought conditions. Some plant characters have opposite signs of h and l indicating
the presence of duplicate type of epistasis. Some plant traits showed [i], [j] and [l] type of
interactions together which indicated complex inheritance of these traits.
For generation variance analysis a model incorporating DE (additive and environmental)
components gave the best fit for all the traits in the crosses-1(NIAB-78 × CIM-446) and cross-2
(CIM-482 × FH-1000) under both normal and drought conditions except number of sympodial
branches in cross NIAB-78 × CIM-446 under normal conditions where model DFE gave the best
fit. In the generation variance analysis only additive effects were involved in the inheritance of
most studied plant traits but generation means analysis showed that additive, dominance and
epistatic effects were involved in the inheritance of these traits. This inconsistancy may be due to
differences in the estimation precision of the two analyses. Generation means analysis was found
relatively more reliable compared to generation variance analysis
High narrow sense heritability estimates 0.67, 0.66 and 0.65 were observed for number of
sympodial branches, number of bolls per plant and seed cotton yield, respectively for cross-1
(NIAB-78 × CIM-446) under normal conditions and narrow sense heritability estimates 0.79,
0.69 and 0.58 were observed for boll weight, seed cotton yield and relative leaf water content
respectively under drought conditions for cross-1. These high heritability estimates were due to
additive gene effects suggest that these traits can be improved by selection during successive
generations. The narrow sense heritability estimates of infinity generation (F∞) were consistently
higher than F2 generation.
The estimates of genetic correlation coefficients were found greater in value than the phenotypic
correlation coefficient for all the studied plant traits of crosses NIAB-78 × CIM-446 and CIM-
482 × FH-1000 under normal and drought conditions.
Seed cotton yield had positive significant correlation with boll weight, fibre length, fibre
strength, lint percentage and relative water content except fibre fineness, exised leaf water loss,
leaf temperature and leaf area in cross-1 (NIAB-78 × CIM-446) under normal and drought
conditions and in cross-2 (CIM-482 × FH-1000) under normal conditions. Plant height was
positively and significantly correlated with sympodial branches, number of bolls per plant, seed
cotton yield, boll weight, fibre length, fibre strength, lint percentage and relative water content
indicating that these characters can be improved with the improvement in plant height.
145
Negative correlation of relative water content with excised water loss shows that the
genes which help plant to restrict water loss perhaps help maintaining higher relative water
content in leaf. Relative water content and excised leaf water loss are easy and rapid in
measurements hence may be used in screening large segregating populations for evolving
drought resistant cotton cultivars.
On the basis of results summarized above, it is concluded that significant difference were
found among six generations of both the crosses under normal and drought conditions.
Generation means analysis indicated the existence of additive, dominance and epistatic genetic
effects in the inheritance of studied plant traits in both the crosses under both normal and drought
conditions. High narrow-sense heritability in F2 and F-infinity generations, indicating the
possibility of obtaining superior recombinant lines.
146
LITERATURE CITED
Abbas, A., M. A. Ali and T. M. Khan. 2008. Studies on gene effects of seed cotton yield and its attributes in five American cotton cultivars. J. Agri. Soc. Sci. 4: 147-152.
Abro, S. 2003. Study of gene action for quantitative and qualitative traits in upland cotton (Gossypium hirsutum L.). M.Sc. Thesis submitted through the Department of Plant Breeding & Genetics to Sindh Agri. Univ. Tandojam.
Ackerson, R.C. 1980. Stomatal response of cotton to water stress and Abscisic Acid as affected by water stress history. Plant Physiology, 65: 455-459.
Afarinesh, A., E. Farshadfar and R. Choukan. 2005. Genetic analysis of drought tolerance in maize (Zea mays L.) using diallel method. Seed Pl. 20(4): 457- 473.
Afiah, S.A.N. and Ghoneim. 2000. Correlation, step wise and path coefficient analysis in Egyptian cotton under saline conditions. Arab Uni. J. Agri. Sci. 8(2): 607-618.
Aguilar, F., T.P. Leon and H.K. Srivastava. 1980. Correlation between the main yield components and fibre quality in three commercial varieties of cotton (Gossypium hirsutum L.). Turrialba, 30(3): 308-311.
Akbar, M., J. Ahmad and F.M. Azhar. 1994. Genetic correlation, path coefficient and
heritability estimates of some important plant traits in upland cotton. Pak. J. Agric. Sci. 3 1(1): 47-50.
Ahmad, I. and J. A. Hellebust. 1988. The relationship between inorganic nitrogen metabolism and proline accumulation in osmoregulatory responses of two eurythaline microalgae. Plant physiol. 88: 348-354.
Ahmad, I., A. Ali, M. Zubair and I.A. Khan. 2001. Mode of gene action controlling seed cotton yield and various components in Gossypium hirsutum L. Pak. J. Agric. Sci. 38(3/4):19-21.
Ahmad, R.T., I.A. Khan and M. Zubair. 1997. Diallel analysis for seed-cotton yield and its contributing traits in upland cotton (Gossypium hirsutum). Ind. J. Agric. Sci. 67(12): 583-585.
Ahmed, H.M., M.M. Kandhro, S. Laghari and S. Abro. 2006. Heritability and genetic advance as selection indicators for improvement in cotton (Gossypium hirsutum). J. Biol. Sci.6(1): 96-99.
147
Ahmed, N., M.A. Chowdhry, I. Khaliq and M. Maekawa. 2007. The inheritance of yield and yield components of five wheat hybrid populations under drought conditions. IJAS, 8(2): 53-59.
Ahmed, H.M., T.A. Malik and M.A. Choudhary. 2000. Genetic analysis of some physiomorphic
traits in wheat under drought. JAPS, 10(1-2): 5-7.
Ahuja, S.L., D. Monga, O.P. Tuteja, S.K. Verma, L.S. Dhayal and Y. Dutt. 2004. Association
and path analysis in the selections made from colour linted Gossypium hirsutum cotton
germplasm. J. Cotton Res. Development, 18(2): 137-140.
Akter. J., M. S. Islam., A. A. Sajib., N. Ashraf., S.Haque and H. Khan. 2008. Microsatellite
markers for determining genetic identities and genetic diversity among jute cultivars.
Australian Journal of Crop Sci. 1(3): 97-107.
Akhtar, M. M., F. M. Azhar and Z. Ali. 2008. Genetic basis of quality attributes in upland cotton
(Gossypium hirsutum L.) germplasm. Int. J. Agri. Biol. Vol. 10(2) 217-220.
Alam, A. and H. Islam. 1991. Correlation and path coefficient analysis of yield and yield contributing characters in upland cotton (Gossypium hirsutum Linn.). Ann. Bangladesh Agric. 1(2) 87-90.
Alam, Z. 1995. Path coefficient and correlation analysis in some elite genotypes of G. hirsutum L. under Faisalabad conditions. Al-Rawi, K.M., H.M. Al-Bayaty and M.J. Layla. 1986. Heritability and path coefficient
analysis for some characters in upland cotton (G. hirsutum L.). Mesopotamia J. Agric. 18(1): 23-32.
Ali,M.A. and S.I. Awan,2009. Inheritance pattern of seed and lint traits in cotton (Gossypium Hirsutum). Int.J.Agric. Biol.11:44-48.
Ali, B., I.A. Khan and K. Aziz. 1998. Study pertaining to the estimation of variability, heritability and genetic advance in upland cotton. Pak. J. Biol. Sci. 1(4): 307-308.
Alishah, O., M.N. Bagherieh-Najjar and L. Fahmideh. 2008. Correlation, Path coefficient and factor analysis of some quantitative and agronomic traits in cotton (Gossypium hirsutum L.), Asian J. Biol. Sci. ISSN 1996-3351.
148
Ali, M.A., I.A. Khan, S.I. Awan, S. Ali and S. Niaz. 2008. Genetics of fibre quality traits in
cotton (Gossypium hirsutum L.). Austral. J. Crop Sci. 2(1):10-17.
Ali, Y., G. Sarwar, Z. Aslam, F. Hussain and T. Rafique. 2005. Evaluation of advanced rice germplasm under water stress environment. Int. J. Environ. Sci. Technol. 2(1): 27-33.
Amutha, K.T.S. Raveendran and D. Krishadoss. 1996. Path analysis in coloured linted cotton
varieties. Madras Agric. J. 83(11): 693-696.
Ansari, A.H.; S.M. Qayyum; M.I. Sohu; M.M. Baig and M.K.K. Rajput. 1991. The influence of
seeding dates on the yield, its components and their interrelation in cotton (Gossypium
hirsutum L). Sarhad J. Agric. 7(2): 11-19.
Araghi, S.G. and M.T. Assad. 1998. Evaluation of four screening techniques for drought resistance and their relationship to yield reduction ratio in wheat. Euphytica, 103: 293–299.
Arshad, M., M. Hanif, Noor-Ilahi and S.M. Shah. 1993. Correlation studies on some commercial cotton varieties of G. hirsutum L. Sarhad J. Agri. 1(12): 49-53.
Ashokkumar, K. and R. Ravikesavan. 2008. Genetic studies of combining ability estimates for seed oil, seed protein, and fibre quality traits in upland cotton (Gossypium hirsutum L.). Res. J. Agric. Biol. Sci. 4(6): 798-802.
Ashour, B.M., A. Arzani, A. Rezaei and S.A.M.M. Maibody. 2006. Study of inheritance of yield and related traits in five crosses of bread wheat (Triticum aestivum L.). J. Sci. Technol. Agri. Natural Resources, 9(4): 123-136.
Ashraf, M. and S. Mehmood. 1990. Response of four Brasssica species to drought stress. Environ. Expt. Bot. 30: pp. 93-100.
Ashraf, M., M. H. Bokhari and S. N. Chishti. 1992. Variation in osmotic adjustment of accessions of lentil (Lens Culinaris Medic.) in response to drought stress. Acta Bot. Neerl. 41: 5 1-62.
Asif, M., M. Rahman., J. I. Mirza and Y. zafar. 2009. Parentage confirmation of cotton hybrids using molecular markers. Pak. J. Bot. 41(2): 695-701.
Aspinall, D. K. V. M. paramaswaran and R. D. Graham. 1983. Proline accumulation in grains, floral organs and flage leaves of wheat and barley in response to variation in water and nitrogen supply. Irrigation Sci. 4: 157-167.
149
Athar, H. R. and M. Ashraf. 2005. Photosynthesis under drought stress. In: Hand Book Photosynthesis, 2nd edition, M. Pessarakli (ed.), C.R.C. Press, New York, USA, pp: 795-810.
Azhar, F.M. and M.A. Khan. 1992. Path coefficient in Gossypium hirsutum L. The Pak. Cottons. 34: 105-106. Azhar, F.M. and S.U.K. Ajmal. 1999. Diallel analysis of oil content in seed of Gossypium hirsutum L. J. Genet. Breed. 53: 19-23.
Azhar, F.M., M. Naveed and A. Ali. 2004. Correlation analysis of seed cotton yield with fiber haracteristics in Gossypium hirsutum L. Int. J. Agri. Biol. 6(4): 656–658.
Badr, S.S.M and M.A.A. Aziz. 2000. Comparative study of fibre properties and yield of five new Egyptian cotton cultivars. Egyptian J. Agric. Res. 78(1): 279-291.
Ball, R.A., M.O. Derrick and A. Mauromoustakos. 1994. Growth dynamics of cotton plant during water-deficit stress. Agron. J., 86: 788-795.
Baloch, M.J., A.R. Lakho and M. Salongi. 1992 Unidirectional and alternate path impacts of yield components on seed cotton yield of Gossypium hirsutum. The Pak Cotton, 36(3-4): 107-114.
Baloch, M.J., A.R. Lakho, H. Bhutto and M.Y. Solangi. 2001. Path coefficient analysis for
assesing direct and indirect effects on yield in Gossypium hirsutum. J. Biol. Sci. 1(5): 354-355.
Barrs, H.D. and P.E. Weatherly. 1962. A re-examination of the relative turgidity technique for
estimating water deficit in leaves. Aust. J. Biol. Sci. 15: 413-428. Basnayake J, cooper M, Ludlow MM, Henzell RG, Snell PJ. 1995. Inheritance of osmotic
adjustment to water stress in three grain sorghum crosses. Theor. Appl. Genet. 90: 675-682.
Basal, H., P. Bebeli, C.W. Smith, and P. Thaxton. 2003. Root growth parameters of
converted race stocks of upland cotton and two BC2F2 Populations. Crop Sci. 43:1983–1 988.
Basal, H., C.W. Smith, P.M. Thaxton, and J.K. Hemphill. 2005. Seedling drought tolerance in upland cotton. Crop Sci. 45:766–771.
Beck, D. L., S. K. Vasal and J. Crossa. 1990. Heterosis and combining ability of CIMMYT’s tropical early and intermediate maturity maize germplasm. Maydica. 35: 279-285.
150
Bertini, C. H. C. M., I. Schuster., T. Sediyama., E. G. Barros., and M. A. Moreira. 2006. Characterization and genetic diversity analysis of cotton cultivars using microsatellites Genetics and Molecular Biol. 29 (2): 32 1-329.
Bertini, C.H.C.D., F.P. da Silva, R.D. Nunes and J.H.R. dos Santos. 2001. Gene action,heterosis and inbreeding depression of yield characters in mutant lines of upland cotton. Pesquisa Agropecuaria Brasileira, 36(7): 941-948.
Bhatnagar, S. 1995. Correlation studies of yield, yield contributing and qualitative characteristics of segregating and stable materials of cotton. Haryana Agric. Univ. J. Res. 25(4): 187-193.
Bhatt, J.G. and R. Andal. 1979. Variation in foliar anatomy of cotton. Proc. Ind. Acad. Sci. 8: 451-453.
Bhutta, W.M., M. Ibrahim and Tahira. 2006. comparison of water relations and drought related flag leaf traits in hexaploid spring wheat (Triticum aestivum L.). Plant Soil Environment. 52:234-238.
Bing, T., C.E. Watson, J.C. McCarty and R.G. Greecr. 1996. Evaluation of genetic variances and correlation for yield and fibre traits among cotton F2 hybrid populations. Euphytica. 91(3): 315-322.
Biswas, G.C.G., A.G. Garcia and G.B. Begonia. 1986. Agronomic and morphological response of different cotton varieties to water deficit. Philipine J. Crop Sci., 11(supplement 1)[Pl.Br.Abst.1988,6:565].
Baloch, M.J. 2004. Genetic variability and heritability estimates of some polygenic traits in upland cotton. Pakistan-Journal-of-Scientific-and-Industrial-Research. 2004; 47(6): 451-454
Blum, A. and A. Ebercon. 1976. Genotypic responses in sorghum to drought stress. III. Free proline accumulation and drought resistance. Crop Sci.16:428-431.
Bocharova, V.M. 1980. Correlation between fibre length and both fineness and strength of fibre in cotton in the F2 . [Pl. Br. Absts. 51 (5): 4384; 1981].
Bot, A. j., F. O. Nachtergaele And A. Young. 2000. Land resources potential and constraints at regional and country level. World Soil Resources Report 90. Land and Water Development Division, FAO. Rome.
Boyer, J.S. 1970. Differing sensitivity of photosynthesis to low water potentials in Corn and Soyabean. Plant physiol. 46: 236-239.
Burke, J.J. 2007. Evaluation of source leaf responses to water-deficit stresses in cotton using a noval stress bioassay. Plant physiology, 143: 108-121.
Carvalho, L.P.D. 2001. Genotypic, phenotypic and environmental correlation between some
characters in upland coloured cotton. Embrapa Algodao. 174: 58107-720.
Carvalho, L.P.D., C.D. Cruz and C.F.D. Moraes. 1994. Genotypic, phenotypic and environmental correlation in cotton (Gossypium hirsutum L.). (Pl. Br. Absts. 66(5): 5390).
Chandra, D., M.A. Islam and N.C.D. Barma. 2004. Variability and interrelationship of nine quantitative characters in F5 bulks of five wheat crosses. Pak. J. Biol. Sci. 7(6): 1040-1045.
Chandio, M.A., M.S. Kalwar and G.M. Baloch. 2003. Gene action for some quantitative characters in upland cotton. Pak. J. Sci. Ind. Res. 46 (4): 295-299.
Channa, H.M. and M. Ahmad. 1982. Correlation studies in some economic and morphological characters of Gossypium hirsutum L. The Pak. Cottons, 26(2): 79-9 1.
Chen, B.J. and L.Y. Zhao. 1991. Multiple correlation analysis of yield, fibre quality and plant characteristics in upland cotton. P.K.V. Res. J. 23(1): 21-23.
Christiansen, M. N. and C. F. Lewis. 1982. Breeding plants for less favourable environments. Published by John Wiley and Sons, New York, USA: 193.
Chun-yan, W., I. Akihiro, L. Mao-song and W. Dao-long. 2007. Growth and eco-physiology performance of cotton under water stress conditions. Agriculturasl Scinces in China, 6 (8): 949-955
Clark J.M. and T.M. McCaig. 1982. Excised leaf water retention capability as indicator of drought resistant in wheat. Crop Sci. 22: 503-506.
Cook, C.G. and K.M. El-Zik. 1993. Fruiting and lint yield of cotton cultivars under irrigated and non-irrigated conditions. Field Crops Res. 33(4): 411-421.
Dedio, W. 1975. Water relations in wheat leaves as screening tests for drought resistance. Can. J. Pl. Sci. 55: 369-378.
Dedio, W., D.W. Stewart and D.G. Green. 1976. Evaluation of photosynthesis measuring methods as possible screening techniques for drought resistance in wheat. Can. J. Pl. Sci. 56: 243-247.
152
Desalegn Z., N. Ratanadilok and R. Kaveeta. 2009. Correlation and heritability for yield and fiber quality parameters of Ethiopian cotton (Gossypium hirsutum L.) estimated from 15 crosses. Kasetsart J. (Nat. Sci.), 43: 1-11.
Desphande, L.A., G.R. Vyahalkar, A.S. Asingkar, and S.S. Mane. 1984. Nature of gene action for yield and fibre traits in upland cotton. Indian J. Agri. Sci. 54(2): 97-99.
Deshphande, L. A. 1978. Genotypic, phenotypic and environmental correlation coefficient in Gossypium hirsutum L. Cotton Res. Bull. Marath Wada Agric. Uni. 2(12): 155-157
Dhanda, S.S., A.P. Tyagi and D.S. Jatsra. 1984. Character association among quantitative and
quality attributes of upland cotton. Ind. J. Agri. Sci. 54(1): 24-29. Dhanda, S. S., G. S. Sethi and R. K. Behl. 2004. Indices of drought tolerance in wheat genotypes at early stages of plant growth. J. Agron. Crop Sci. 190: 6-12.
Dhanda, S.S. and G.S. Sethi. 2002. Tolerance to drought stress among selected Indian wheat cultivars. J. Agri. Sci. 139:319-326.
Dhanda, S.S. and G.S. Sethi. 1998. Inheritance of excised leaf water loss and relative water content in bread wheat (Triticum aestivum). Euphytica . 104: 39-47.
Dhillon, S.S. and T.H. Singh. 1980. Genetic control of some quantitative characters in upland cotton (Gossypium hirsutum L.). J. Agric. Sci., U.K. 94(3): 539-543.
Dodig. D., M. Zori, B. Kobiljski, G. S. Momirovi, and S. A. Quarrie.Assessing drought tolerance and regional patterns of genetic diversity among spring and winter bread wheat using simple sequence repeats and phenotypic data. Crop & Pasture Science, 61: 812–824. 2010.
Dubey, L., B. M. Prasanna., B. Ramesh. 2009. Analysis of drought tolerant and susceptible maize genotypes using SSR markers tagging candidate genes and consensus QTLs for drought tolerance. Indian J. Genet. Pl. Breed. 69(4). pp. 344-351.
Echekwu. C.A. 2001. Correlation and correlated responses in upland cotton (Gossypium hirsutum L.). Tropicaltura, 19(4): 210-213.
El-Fawal, M.A., A.M. Gad, A.A.A. Bary, and A.A. El-Khishen. 1974. Studies on gene action in
an interspecific cross of cotton. II estimation of genetic variance and heritability. Egyptian J. Genet. Cytol. 3(2): 236-245.
El-Moneim, A.M.A. and A.H. Belal. 1997. Estimating of some breeding parameters in durum wheat under low rainfed conditions in North Sinai, Egypt. Ann. Agric. Sci. Moshtohor, 35(4): 1897-1914
153
El-Seidy, E.H. 1997. Estimation of genetic effects for some agronomic traits in barley under water stress and non-stress condition. Ann. Agric. Sci. Moshtohor, 35(3): 1147-1164. Ennahli, S and H.J. Earl. 2005. Physiological limitations to photosynthetic carbon assimilation in cotton under water stress. Crop Sci., 45: 2374-2382.
Erkling, A and M. Karaca. 2005. Assessment of Genetic Variation in Some Cotton Varieties (Gossypium hirsutum L.) Grown in Turkey Using Microsatellite.Akdeniz.uni.fak.der. 18(2): 201-206.
Esmail, R.M. 2007. Genetic analysis of yield and its contributing traits in two intra specific cotton crosses. J. Appl. Sci. Res. 3(12): 2075-2080.
Esmail, R.M., F.A. Hendawy, M.S. Rady and A.M. Hamid. 1999. Genetic studies on yield and yield components in one inter and two intra specific crosses of cotton. Egyptian J. Agron. 21: 37-51.
Falconer, D.S. and T.F.C. Mackay. 1996. Introduction to Quantitative Genetics. Chapman and Hall, London.
Farooq, M., A. Wahid, N. Kobayashi, D. Fujita and S. M. A. Basra. 2009. Plant drought stress: effects, mechanisms and management. Agron. Sustain. Dev. 29: 185-212.
Farshadfar, E., S. Mahjouri and M. Aghaee. 2008. Detection of epistasis and estimation of additive and dominance components of genetic variation for drought tolerance in durum wheat. J. Biol. Sci. 8(3): 598-603.
Frederick. J. R., C. R. Camp and P. J. Bauer. 2001. Drought-Stress Effects on Branch and Mainstem Seed Yield and Yield Components of Determinate Soybean Crop Science 41:759-763.
Gad, A.M., M.A. El-Fawal, M.B. Bashir, A.A. El-Khishen. 1974. Studies on gene action in an
interspecific cross of cotton. I. Manifestation of types of gene effects. Egyptian J. Genet. Cytol. 3(1): 117-124.
Ganapathy, K.N., Y. Sreedhar and M. Gunasekaran. 2006. Character association and component analysis for yield and fibre quality traits in upland cotton (Gossypium hirsutum L.). Crop Res. Hisar, 32(2): 225-229.
Gent, M. P. N.,and Kiomoto, R. K. 1992. Canopy photosynthesis and respiration in winter wheat adapted and unadapted to Connecticut. Crop Sci. 32: 425-431.
Gerik, T.J. K.L. Faver, P.M. Thanton and K.M. El-Zik. 1996. Late season water stress in cotton- 1. Crop Sci. 36(4): 914-921.
154
Gohil, V.N., H.M. Pandya and D.R. Mehta. 2006. Genetic variability for seed yield and its component traits in soybean. Agric. Sci. Digest, 26(1): 73-74.
Gill, M.S. and H.S. Kalsy. 1981. Genetic analysis in four crosses of upland cotton. Crop. Imp.
8(2): 95-99. Giri, A.N. and U.C. Updhyay. 1980. Correlation and regression studies in upland cotton under
different patterns and intercropping systems. Ind. J. Agri. Sci. 50(12): 907-910. Gite, V.K., M.B. Misal and H.V. Kalpande. 2006. Correlation and path analysis in cotton (Gossypium hirsutum L.). J. Cotton Res. Dev. 20(1): 215-218.
Golabadi, M., A. Arzani and S.M.M. Maibody. 2005. Evaluation of variation among durum wheat F3 families for grain yield and its components under normal and water-stress field conditions. Czech J. Genet. Pl. Breed. 41: 263-267.
Golparvar, A.R., I.M. Haravan., F. Darvish; A. M. Rezaie and A.G. Pirbalouti. 2004. Genetic assessment of some morpho-physiological traits in bread wheat under drought stress conditions. Pajouhesh va Sazandegi Agron. Horti. (62): 90-95.
Gomaa, M.A.M, A.M.A. Shaheen and S.A.M. Khattab. 1999. Gene action and selection indices in two cotton (Gossypium barbadense L.) crosses. Ann Agric. Sci. Cairo. 44(1): 293-308.
Gomaa, M.A.M. 1997. Genetic studies on yield, yield components and fiber properties in three Egyptian cotton crosses. Ann. Agric. Sci. Cairo, 42(1): 195-206.
Govt. of Pakistan, 2000. Economic Survey of Pakistan, Finance Division, Economic Advisory Wing, Islamabad, Pakistan.
Govt. of Pakistan.2009-10. Economic Survey of Pakistan, Finance Division, Economic Advisory Wing, Islamabad, Pakistan.
Guang, C., and D. X. Ming. 2006. Genetic diversity of source germplasm of upland cotton in China as determined by SSR marker analysis. Acta genetica sinica. 33(8): 733-745
GuangMei, Y and Z. Zheng. 2003. A comparative study of drought resistance in maize genotypes of Guizhou. J. Mountain Agri. Biol. 22(2): 110-113.
Guinn, G., and J. R. Mauney. 1984a. I. Effect of moisture stress on flowering. Agron. J. 61: 769-773.
Gulzar. K., S. Saghera and, G. A. Parray Skuast.2010. Variation for drought tolerance in hill rice genotypes. Crop improvement, 37(1): 21-24.
155
Guo, W. Z., Bao-Liang Zhou., Lu-Ming Yang., Wei Wang and Tian-Zhen Zhang. 2006.Genetic Diversity of Landraces in Gossypium arboreum L. Race sinense Assessed with Simple Sequence Repeat Markers. J. Int.Plant Biology. 48 (9): 1008-1017.
Gupta, A.S. and G.A. Berkowitz. 1987. Osmotic adjustment, symplast volume, and non-stomatal mediated water stress inhibition of photosynthesis in wheat. Pl. Physiol. 85: 1040-1047.
Haider, S. and M.A. Khan. 1998. Genotypic and phenotypic correlation analysis of some quality characters and yield of seed cotton in upland cotton (Gossypium hirsutum). Pak. J. Biol. Sci. 1(3): 235-236.
Hall, A. J., D. J. Conner, and D. M. Whitefield. 1990. Root respiration during grain filling in Sunflower. The effect of water stress. Plant and Soil. 12(1):57-66.
Harris, J. A. 1912. A simple test of goodness of fit of Mendelian ratios. Am. Nat., 46: 741-745.
Hassan, G., G. Muhammad. U.K. Naqub and A. Rehman. 1999. Combining ability and heterosis in a diallel cross of cotton (Gossypium hirsutum L.). Sarhad J. Agri. 15: 563-568.
Hayman, B.I. 1954. The theory and analysis of diallel crosses. Genetics, 39: 789-809.
Heatherly, L.G; W.J. Russell and T.M. Hinckley. 1977. Water relations and growth of soybeans in dry soil. Crop Sci. 17(3): 381-386.Hendawy, F.A., M.S. Rady, A.M. Abd-el-Hamid and R.M. Ismail. 1999. Inheritance of fibre traits in some cotton crosses. Egyptian J. Agron. 21: 15-36.
Hendawy, F.A., M.S. Rady, A.M. Abd-el-Hamid and R.M. Ismail. 1999. Inheritance of fibre traits in some cotton crosses. Egyptian J. Agron. 21: 15-36.
Herring, A.D., D.L. Auld, M.D. Ethridge, E.F. Hequet, E. Bechere, C.J. Green and R.G. Cantrell. 2004. Inheritance of fiber quality and lint yield in a chemically mutated population of cotton. Euphytica, 136(3): 333-339.
Hirt, H. and Shinozaki, K. (2004). Plant responses to abiotic stress. Springer Verlag Berlin.
Human, J. J., and Toit. 1990. The influence of plant water stress on net photosynthesis and yield of sunflower (Helianthus annus L.) Ind. J. Agric. Sci. 164(94)231-241.
Hussain, M., F.M. Azhar and A. A. Khan. 2008. Genetic basis of variation in leaf area, petiole length and seed cotton yield in some cotton (Gossypium hirsutum L) genotypes. Int. J. Agric. Biol., 6 (10): 705-708.
156
Hussain, I. 2009. Genetics of Drought Tolerance In maize(Zea Mays L). Ph.D Thesis, Deptt. P.B.G., Univ. Agri., Faisalabad, Pakistan.
Hussain, S.S., F.M. Azhar, and M. Sadiq. 1998. Genetic correlation, path coefficient and
heritability estimates of some important plant traits of upland cotton. Sarhad J.Agri. 14(1): 57-59.
Hussain, S.S., F.M. Azhar and M. Sadiq. 2000. Association of yield with various economic
characters in Gossypium hirsutum. Pak. J. Bio. Sci. 3(8): 1237-1238. Inamullah, F. Mohammad, G. Hassan, S. Din and S. Akbar. 2005. Genetics of important traits in
bread wheat using diallel analysis. Sarhad J. Agri. 21(4): 617-622.
Iqbal. K,. F. M. Azhar , I. A. Khan and E. ullah. 2010. Assessment of cotton (Gossypium hirsutum) germplasm under water stress condition. Int. J. Agric. Biol.,12:251-255.
Iqbal. K,. F. M. Azhar , I. A. Khan and E. ullah. 2011. Variability for drought tolerance in cotton (Gossypium hirsutum) and its genetic basis. Int. J. Agric. Biol.,13:61-66.
Iqbal, M. 2002. Inheritance and combining ability studies for earliness, yield and yield components in 6 x 6 intra-specific hybrids of Gossypium hirsutum L. Ph.D. Thesis submitted through the department of Plant Breeding and Genetics to the Sindh Agri. Univ. Tando Jam
Iqbal. M. Z and M. A. Nadeem. (2003). Generation mean analysis for seed cotton yield and number of sympodial branches per Plant in cotton (Gossypium hirsutum L.). Asian Journal of Plant Sciences 2 (4): 395-399.
Iqbal, M., K. Hayat, R.S.A. Khan, A. Sadiq and N. Islam. 2006. Correlation and path coefficient analysis for earliness and yield traits in cotton (G. hirsutum L.). Asian J. Pl. Sci. 5(2): 341-344.
Irum , A. , A. Tabasum and M. Z. Iqbal. 2011. Variability, correlation and path coefficient alysis of seedling traits and yield in cotton (Gossypium hirsutum L) African J. Agri. Biot. Vol. 10(79), pp. 18104-18110.
Isoda, A. and Inamullah. 2005. Adaptive responses of soybean and cotton to water stress: I. Transpiration changes in relation to stomatal area and stomatal conductance. Plant Production Science, 8 (1): 16-26.
Jackson, B. S. and Gerik. T. J. (1990) Boll shedding and boll load in nitrogen stressed cotton. Agron. J. 82:483-488.
Jafar ,M. S. , G. Nourmohammadi and A. maleki. 2004. 4th International Crop Sci. Congress (ICSC), Birsbane, Australia. Sep. 26-Oct.1st.
157
Jagtap, D.R. and S.S. Mehetre. 1998. Genetic variability in intervarietal crosses of Upland cotton (Gossypium hirsutum L.). Anna. Agri. Res. 19: 130-132.
Johnson, H. W., H. F. Robinson and R.E. Comstock. 1955. Estimates of genetic and
environmental variability in soybean. Agron. J. 47 : 314-318.
Joshi, A.K; G.V. Marviya and C.J. Dangaria. 2005. Identification of drought tolerant inbred lines of pearl millet. Inter. Sorghum Millets Newsletter. 46: 100-102.
Juan, M. F., X. X. yang, H. F Lan and LI Jing-fu. 2010. Analysis of genetic diversity in cultivated and wild tomato varieties in Chinese market by RAPD and SSR. Agricultural Sciences in China. 9(10): 1430-1437.
Kalsy, H.S. and H.R. Garg. 1988. Analysis of generation means for metric traits in upland cotton (Gossypium hirsutum L.). Ind. J. Agric. Sci. 58(5): 397-399.
Kar, M., B. B. Patro, C. R. Sahoo and B. Hota. 2005. Traits related to drought resistance in cotton hybrids. Ind. J. Pl. Physiol. 10(4): 377-380.
Karad, S.R., P.N. Harer, D.D. Kadam and R.B. Shinde. 2005. Genotypic and phenotypic variability in soybean (Glycine max L.). J. Maharashtra Agric. Uni. 30(3): 365-367.
Karademir, C., E. Karademir., R. Ekinci and O. Gencer. 2009. Correlation and path coefficient analysis between leaf chlorophyll content, yield and yield components in cotton ( Gossypium hirsutum L.) under drought stress conditions. Not. Bot. Hort. Agrobot. Cluj. 37(2): 241-244.
Keerio, M.D.; M.S. Kalwar; M.I. Memon and Z.A. Soomro. 1995a. Genetics of seed cotton yield and its primary components in Gossypium hirsutum L. Pak. J. Bot. 27(2): 425-429.
Kaseem, E.S., M.A. Khalifa, M.A. El-Morshidy and F.G. Younis. 1984. Genetical analysis of some agronomic characters in cotton. II. Yield and its components. Agric. Res. Review. 59(9): 62-82.
Kashiwagi, J., L. Krishnamurthy, H. D. Upadhyaya, H. Krishna, S. Chandra, V. Vadez and R. Serraj. 2004. Genetic variability of drought avoidance root traits in the mini-core germplasm collection of chickpea (Cicer arietinum L.). Euphytica. 146: 213-222.
Kaul, R. 1974. Potential net photosynthesis in flag leaves of severely drought stressed wheat cultivars and its relationship to grain yield. Cand. J. Pl. Sci. 54: 811-815.
Kauser, R., H. R. Athar, and M. Ashraf. 2006. Chlorophyll fluorescence: A potential indicator for rapid assessment of water stress tolerance in canola (Brassica napus L.). Pak. J. Bot., 38 (5): 1501-1509.
158
Kaushik, S.K., D.L. Singhania and C.J. Kapoor. 2005. Correlation and path analysis among different traits in upland cotton (Gossypium hirsutum L.). J. Cotton Res. Development, 19(2): 140-144.
Keriege, D.R. (1997). Genetics and environmental factors affecting productivity of cotton. In: Dugger, P. and Richter. D.A (ed.) Proc Beltwide cotton conf., New P.1347.
Koscienlniak, J. and F. Dubert. 1985. Biological indices of productivity of various breeding lines of maize. III. Correlation between simple and final yield of grain and dry matter under natural conditions of vegetative growth. Acta. Agra. Silvestria. Ser. Agra. 24: 35- 48.
Krieg, D.R., and J.F.M. Sung. 1986. Source-sink relationships as affected by water stress during boll development. p. 73–77. In J.R. Mauney and J.M. Stewart (ed.) Cotton physiology. The Cotton Foundation, Memphis, TN Khan A.I. and F.M. Azhar. 2000. Estimates of heritabilities and pattern of association among
different characters of Gossypium hirsutum L. Pak. J. Agric. Sci. 37(1-2).
Khan, M.A., Z.A. Soomro and N. Leghari. 2003. Diallel analysis for yield and yield contributing characters in Gossypium hirsutum L. Pak. J. Applied Sci. 3(2): 129-1 32. Khan, M.D., C.N. Ahmed and M. Saleem. 1980. Association of various characteristics in parents and hybrids of Gossypium hirsutum L. The Pak. Cottons, 24(3): 253-261. Khan, M.D., M.A. Khan and M.A. Khan. 1977. Correlation studies of height with development and economic characters in G. hirsutum L. The Pak. Cottons. 22 (1): 19-20. Khan, M. A., H. A. Sadaqat and M. Tariq. 1991. Correlation analysis in cotton. (Gossypium
hirsutum L.) Pak. J. Agi. Res. 29(2): 177-183. Khan, I. A., S. Habib, H. A. Sadaqat and M. H. N. Tahir. 2004. Selection criteria based on seedling growth parameter in maize varies under normal and water stress conditions. Int. J. Agri. Biol. 6(2): 252-256.
Khan, N.U., G. Hassan, K.B. Marwat, Farhatullah, M.B. Kumbhar, A. Parveen, Umm-E-Aiman,
M.Z. Khan and Z.A. Soomro. 2009. Diallel analysis of some quantitative traits in
Gossypium hirsutum L. Pak. J. Bot., 41(6): 3009-3022.
Khan. A. I.,Y-B. Fu and I. A. Khan. 2009. Genetic diversity of Pakistani cotton cultivars as revealed by simple sequence repeat markers. Communication in. Bio and Crop. Sci. 4 (1)pp-21-30
159
Khan, I. A., F. S. Awan, A. Ahmad and A. A. Khan. 2004. A modified mini-prep method for economical and rapid extraction of genomic DNA in plants. Plant Molecular Biology Report 22: 89a-89e.
Khan, M.A., A.S. Larik and Z.A. Soomro. 2002. Study of gene action for yield and yield components in Gossypium hirsutum L.. Asian J. Pl. Sci. Volume I No. 2 : 130–131.
Khan, M. Q., S. Anwar., and M. I. Khan. 2002. Genetic variability for seedling traits in wheat ( Triticum aestivum L. ) under moisture stress conditions. Asian. J. Plant Sci.,5: 588-590.
Khan A.I. and F.M. Azhar. 2000. Estimates of heritabilities and pattern of association among
different characters of Gossypium hirsutum L. Pak. J. Agri. Sci. 37(1-2).
Khan, I.A., A. Shakeel and F.M. Azhar. 2001. Genetic Analysis of Fibre Quality Traits in
Kiani G., G. A. Nematzadeh, S. K. Kazemitabar and O. A. Shah. Combining ability in cotton cultivars for agronomic traits. Int. J. Agri. Biol. 09(3): 521-522.
Kll, F., L. Efe and S. Mustafayev. 2005. Genetic and environmental variability in yield, yield components and lint quality traits of cotton. Int. J. Agri. Biol. 7(6): 1007-1010.
Kramer, P. J., in Linking research to Crop Production (eds Staples, R. C. and Kuhr, R. J.), Plenum Press, New York, 1980, pp. 51–62.
Kumar A. and S.C. Sharma. 2007. Genetics of excised-leaf water loss and relative water content in bread wheat (Triticum aestivum L.). Cereal Res. Commun. 35(1): 43-52.
Kumar, A. and D. P. Singh. 1998. Use of physiological indices as a screening technique for drought tolerance in oilseed Brassica species. Ann. Bot. 81: 413-420.
Kumar, R., M. Singh, M.S. Narwal and S. Sharma. 2005. Gene effects for grain yield and its attributes in maize (Zea mays L.). Nat. J. Pl. Improv. 7(2): 105-107.
Kumaresan, D., J. Ganesan and S. Ashok. 2000. Genetic analysis of quantitative characters in cotton (G. hirsutum L). Crop Res. Ind. 19(3): 481-484.
Kumari,-S-R; Chamundeswari,-N. 2005.Studies on genetic variability, heritability and genetic advance in cotton (Gossypium hirsutum L.). Research-on-Crops. 2005; 6(1): 98-99
Kumari, S.R., P. Subbaramamma and A.N. Reddy. 2005. Screening of cotton (Gossypium hirsutum L.) genotypes for drought tolerance under rainfed conditions in black cotton soils. Ann. Agric. Res. 26(2): 270-274.
160
Kumari, S.R., P. Subbaramamma. 2006. Genetic evaluation ofGossypium hirsutum genotypes for yield, drought parameters and fibre quality. J. cotton Res. Dev. 20(2): 166-170.
Kyei, P.M. 1968. Correlation between various characters in upland cotton varieties. Res. Rup. Deve. Suwarn. 2(1): 109-122.
Lafitte, H. R., A. H. Price and B. Courtois, 2004. Yield response to water deficit in an upland rice mapping population: associations among traits and genetic markers. Theor. Applied Genet., 109: 1237-1246.
Lancon, J.E. Goze, B. Hau, M. Bachelier and J.L. Chanselme. 1993. Multisite trait of diallel with four elite parents. Correlation between variables. Cot. Fib. Trop. 48(1): 11-14.
Larik, A.S. A.A. Kakar, M.A. Naz and M.A. Shaikh. 1999. Character correlations and path analysis in seed cotton yield (Gossypium hirsutum L.). Sarhad J. Agri. 15: 269-274.
Le Houerou, H.N .1996. Climate changes, drought and desertification. J. Arid Environ. 34, 133-185.
Lea, P. J., M. A. J. Parry and H. Medrano. 2004. Improving resistance to drought and salinity in plants. Annal. App. Biol., 144: pp. 249-50.
Lee, J.A. 1984. Cotton as a world crop. p. 1–25. In R.J. Kohel and C.F. Lewis (ed.) Cotton. Agron. Monogr. 24. ASA, CSSA, and SSSA, Madision, WI.
Lee, K.C., R.W. Campbell and G.M. Paulsen. 1974. Effect of drought stress and succinic acid-2,2- dimethylhydrazide treatment on water relations and photosynthesis in pea seedling. Crop Sci. 14: 279-282
Leidi, E.O., J.M. Lopez, M. Lopez and J.C. Gutierrez.1993. Searching for tolerance to water stress in cotton genotypes: Photosynthesis, Stomatal conductance and Transpiration. Photosynthtica, 28 (3) : 383-390 [Pl. Br. Abst. 1994, 64 (3):1348].
Leidi, E.O., Lopez. J. Gorham and J.C. Gutierrez. 1999. Variation in carbon isotope discrimination and other traits to drought tolerance in upland cotton cultivars under dryland conditions. Field Crops Res. 61:109-123.
Levitt, J. 1972. Responses of Plants to Environmental Stresses. Academic Press, New York.
Levitt, J. 1980. Responses of Plants to Environmental Stresses, Second Edition, vols. I and II. Academic Press, New York.
161
Levi, A., L. Ovnat, A.H. Paterson and Y. Saranga, 2009. Photosynthesis of cottonnear- isogenic lines introgresses with QTLs for productivityand drought related traits.Plant Sci., 177: 88-96. Lin, Y. and L.Y. Zhao. 1988. Estimation of genetic effects on the main fibre quality
characteristics in upland cotton. Acta Genetica Sinica, 15(6): 401-408.
Liu, J.D., W.W. Ye and B.X. Fan. 1998. Research on stress resistance in cotton and its utilization in China. China Cottons, 25 (3): 5-6.
Lobato, A. K. S., Oliveira Neto, C. F., Santos Filho, B. G., Costa, R. C. L., Cruz, F. J. R., Borges Neves, H. K., Santos Lopez, M. J. 2008. Physiological and biochemical behavior in soybean (Glycine max cv. Sambaiba) plants under water stress. Australian. J. Crop. Sci. 2(1):25-32.
Longenberger, P.S., C.W. Smith, P.S. Thaxton and B.L. McMichael. 2006. Development of a screening method for drought tolerance in cotton seedlings. Crop Sci. 46: 2104-2110.
Ludlow,M. M., and R. C. Muchow. 1990. A critical evaluation of traits for improving crop yields in water limited environments. Adv. Agron. 43: 107-153.
Ma, F.C., Y.Y. Zhou, R.T. Wang, and C.G. Liv. 1983. Genetic analysis of characters in the progeny of inter-varietial hybrid of upland cotton. Acta Agriculturae Universitatis, Pekinensis, 9(4): 27-34.
Mahmood. S., M. Irfan., F. Raheel and A. Hussain. 2006. Characterization of cotton (Gossypium hirsutum L.) varities for growth and productivity traits. Int.J. Agri. Biol. 8 (6):796-800.
Majeed, A., T.A. Malik and A.S. Khan. 2001. Genetic basis of physio-morphic traits related to drought tolerance in barley. JAPS, 11(4): 167-170.
Malik, T.A. and D. Wright. 1995. Genetics of some drought resistant traits in wheat. Pak. J. Agric. Sci. 32 (4): 256-261.
Malik, T.A. and D. Wright. 1998. Morphological traits and breeding for drought resistance in wheat. JAPS, 8 (3-4): 93-99.
Malik, T.A. and D. Wright. 1998. Physiological traits and breeding for drought resistance in wheat. Sarhad J. Agri. 14 (4): 327-334.
Malik, T.A. Sana-Ullah and S. Malik. 2006. Genetic linkage studies of drought tolerant and agronomic traits in cotton. Pak. J. Bot. 38 (5): 1613-1619.
Marani, A. 1973. Effects of soil moisture stress on two varieties of upland cotton in Israel. Exp. Agri. 9 (1): 121-128.
162
Mather, K. and J.L. Jinks. 1982. Biometrical Genetics. 3rd ed. Chapman and Hall Ltd. London, UK.
Mathapati, S.N., K.G. Hiremath, S.N. Kadapa and J.V. Gould. 1978. Genetic variability and correlation of economic characters in Egyptian cotton. J. Agri. Sci. 48(3): 156-158
Matsui, T. and B. B. Singh. 2003. Root characteristics in cowpea related to drought tolerance at
the seedling stage. Exp Agric. 39: 29-38.
Mauney, J. R. (1986). Vegetative growth and development of fruiting sites. In: J. R. Mauney and J. M. Stewart, Editors, Cotton physiology, The cotton foundation publisher, Memphis, TN,USA (1986), pp11-28.
May, O.C. and C.C. Green. 1994. Genetic variation for fibre properties in elite Pee Dee Cotton populations. Crop Sci. 34(3): 684-690.
McCaig, T.N. and I. Romagosa. 1989. Measurement and use of excised leaf water status in wheat. Crop Sci. 29:1140-1145.
McCarty Jr., J.C., J.N. Jenkins and J. Zhu. 1998. Introgression of day-neutral genes in primitive cotton accessions: I. Genetic variances and correlations. Crop Sci. 38(6): 1425-1428. McCarty, J.C., J. Wu and J.N. Jenkins. 2008. Genetic association of cotton yield with its component traits in derived primitive accessions crossed by elite upland cultivars using the conditional ADAA genetic model. Euphytica. 161: 337-352
McMichael, B,L., and J.D. Hesketh. 1982. Field investigations of the response of cotton to water deficits. Field Crop Res., 5: 319-333.
McMichael, B.L. and J.E. Quisenberry. 1991. Genetic variation for root - shoot relationship among cotton germplasm. Environ. Exp. Bot., 31: 461–470.
Memon, S., M. Qureshi, B.A. Ansari and M.A. Sial. 2007. Genetic heritability for grain yield and its related characters in spring wheat (Triticum aestivum). Pak. J. Bot. 39(5): 1503-1509.
Mert, M., O. Gencer, Y. Akscan and K. Boyac. 2003. Inheritance of yield and yield components in cotton (Gossypium hirsutum L.). Turkish J. Field Crops, 8(2): 62-67.
Minhas, R., I. A. Khan, M. S. Anjam and K. Ali. 2008. Genetics of some fibre quality traits among intraspecific crosses of Gossypium. Int. J. Agri. Biol. 10(2): 196-200.
Mirbahar. A. A., G. S. markhand., A .R. mahar.,S. A. abro and N. A. kanhar.2009.Effect of water stress on yield and yield components of wheat (triticum aestivum L.) Varieties. Pak. J. Bot., 41(3): 1303-1310.
163
Mock, J. J and M. J. McNeill. 1979. Cold tolerance of maize inbred lines adapted to various
latitude in North America. Crop Sci. 19: 239-241.
Morrow, M. R., Keriege, D. R. (1990) Cotton management strategies for a short growing season environment: Water-Nitrogen considerations. Agron. J. 82:52-56.
Mukhtar, M.S., T.M. Khan and A.S. Khan. 2000a. Genetic analysis of yield and yield components in various crosses of cotton (Gossypium hirsutum L.). Int. J. Agri. Biol. 02(3): 258-260.
Mukhtar, M.S., T.M. Khan and A.S. Khan. 2000b. Gene action study in some fibre traits in cotton (Gossypium hirsutum L.). Pak. J. Biol. Sci. 03(10): 1609-1611.
Munir, M; M.A. Chowdhry and M. Ahsan. 2007. Generation means studies in bread wheat under drought condition. Int. J. Agri. Biol. 9(2): 282-286.
Munjal, R. and S.S. Dhanda. 2005. Physiological evaluation of wheat (Triticum aestivum L.) genotypes for drought resistance. Ind. J. Genet. Pl. Breed. 65(4): 307-308.
Murtaza, N. 2005. Study of gene effects for boll number, boll weight, and seed index in cotton. J. Cent. Eur. Agri. 6 (3): 255-262.
Murtaza, N., A. Qayyum and M.A. Khan. 2004. Estimation of genetic effects in upland cotton for fibre strength, and staple length. Int. J. Agri. Biol. 6 (1): 61-64.
Murthy J.S.V.S. 1999. Character association and component analysis in upland cotton. Madras Agric. J. 86(1-3): 39-42.
Murthy, J.S.V.S., S.R. Kumari and N. Chamundeswari. 2005. Genetic variability, correlation and path analysis in Gossypium herbaceum cotton under saline soils. J. Cotton Res. Development, 19(2): 148-152.
Murugan, S. and J. Ganesan. 2006. Generation mean analysis in rice (Oryza sativa L.) crosses utilizing 'WA' cytosteriles. Pl. Archives, 6(1): 165-167.
Mu-XiuLing and Bao-Xiao. 2003. Effect of soil water stress on water regime in cotton leaves and on photosynthesis. China Cotton, 30(9): 9-10.
Nachnani, G.H. and H.K. Abro. 1980. Correlation studies of yield with certain physical
characteristics in F3 generations of crosses of Upland cottons. The Pak Cottons, 24(1): 119-129.
164
Nadarajan, N. and S.R.S. Rangasamy. 1990. Combing ability and variability studies in Gossypium hirsutum L. Ind. Society Cotton Improv. J. 15(1): 16-19.
Nadeem, K and F.M. Azhar. (2005). Genetic Analysis of Fibre Length and Strength of Gossypium hirsutum L. Int. J. Agri. Biol., 7 ( 2) : 263-265.
Nemeth, M., T. Janda, E. Horvath, E. Paldi and G Szalai, 2002. Exogenous salicylicacid increase polyamine content but may decrease drought tolerance in maize.Plant Science 162:pp. 569-574.
Nepo-muceno, A.L., D.M. Oosterhuis, and J.M. Stewart. 1998. Physiological response of cotton leaves and roots to water deficit induced by polyethylene glycol. Environ. Exp. Bot., 40 (1): 29-41.
Nezar H. S. 2005. Effects of drought stress on growth and yield of barley. Agronomie . 25(1) : pp. 145-149
Nimbalkar, R.D., A.C. Jadhave and S.S. Mehetra. 2004. Combining ability studies in desi cotton (Gossypium arboreum and Gossypium herbaceum). J. Maharastra, Agric. Uni. 29(2): 166-170.
Nistor, T and G. Nistor. 1999. Inheritance of fibre length in cotton. Analele-Institutului-de-Cercetari-pentru-Cereale-si-Plante-Tehnice-Fundulea, 66: 13-23.
Novoselovic, D., M. Baric, G. Drezner, J. Gunjaca and A. Lalic. 2004. Quantitative inheritance of some wheat plant traits. Genet. Mol. Biol. 27(1): 92-98.
Pace, P.F., H.T. Cralle, S.H.M El-Halwani, and S.A. Senseman. 1999. Drought induced changes in shoot and root growth of young cotton plants. J. Cotton. Sci. 3: 183-187
Patra, B.C., K.C. Pradhan, S.K. Nayak and S.S.C. Patnaik. 2006. Genetic variability in long awned rice genotypes. Environ. Ecology, 24 (1): 27-31.
Pandey, S.K., S.B. Pandey and P. Singh. 2003. Analysis of character association in upland cotton (Gossypium hirsutum L.). Progre. Agri. 3(1-2): 139-140
Patel, U. G., Patel, J. C., Patel, N. N., Patel, A. D. 1996. Variability parameters in diploid cotton. Gujrat, Agricultural University Research Journl. 22 (1): 9-13.
Pathak, R.S. 1975. Gene effects for fibre properties in upland cotton (Gossypium hirsutum L.). Theor. Appl. Genet. 46(3): 129-133.
Pathak, R.S. and R.B. Singh. 1970. Genetics of yield characters in upland cotton. Ind. J. Pl.
Breed. Genet. 30(3): 679-689.
165
Pathan, M. S., P. K. Subudhi, B. Courtois and H. T. Nguyen. 2004. Molecular dissection of abiotic stress tolerance in sorghum and rice. In Physiology and Biotechnology Integration for Plant Breeding. Edited by Nguyen HT, Blum A. Marcel Dekker, Inc. 525-569.
Pavasia, M.J., P.T. Shukla and V. K. Poshiya. 1998. Combining ability for vegetative characters over environments in Upland cotton (G. hirsutum L.). Gujarat-Agricultural-University-Research-Journal. 1998; 23(2): 28-32.
Pavasia, M.J., P.T. Shukla and U.G. Patel. 1999. Combining ability analysis over environments for fibre characters in upland cotton. Ind. J. Genet. Pl. Breed. 59(1): 77-81.
Pereira, J.R., P.D. Fernandes and N.E. De-Macedo-Beltrao. 1998. Germination of genotypes of upland cotton (Gossypium hirsutum L. r. latifolium H.) under water stress. Revista-de-oleaginosas-e-Fibrosas., 2 (1): 41-51.
Pettigrew, W. T. 2004. Physiological consequences of moisture deficit stress in cotton. Crop Sci., 44: 1265-1272.
Pirdashti H., Zeinolabedin Tahmasebi Sarvestani, and Mohammad Ali Bahmanyar. 2009. Comparison of Physiological Responses among Four Contrast Rice Cultivars under Drought Stress Conditions. World academy of science engineering and technology 49.
Pirdashti, H., Z. T. Sarvastani, G. Nematzadeh and A. Ismail. 2004. 4th International Crop Sci. Congress(ICSC), Brisbane, Australia. Sep. 26- Oct.1st.
Poehlman, J. M. and D. A. Sleper 1995. Breeding Field Crops, 4th ed. Lowa State Press, Blackwell publishing company, U.S.A
Prakash, V. and R.P.S. Verma. 2006. Inheritance of grain yield and some quantitative traits in six rowed barley (Hordeum vulgare L.). Ind. J. Genet. Pl. Breed. 66(1): 39-40.
Prasad, U.S., V.C. Reddy and A.N. Reddy. 2005. Studies on genetic variability in American cotton (Gossypium hirsutum L.). Karnataka J. Agric. Sci. 18(4): 1095-1098.
Premachandra, G. S., H. Saneoka, K. Fujita and S. Ogata. 1992. Leaf water relations, osmotic adjustment, cell membrane stability, epicuticular wax load and growth as affected by increasing water deficits in sorghum. J. Exp. Bot., 43:1569-1576.
Punitha,D., T.S. Raveendran and M. Kavitha. 1999. Heterosis and combining ability studies for
quantitative characters in coloured linted cotton genotypes (Gossypium hirsutum x Gossypium barbadense). J. 23: 17-20.
166
Quisenberry, J.E., B, Roark, and B.L. McMichel. 1982. Use of transpiration decline curves to indentify drought-tolerant cotton germ-plasm. Crop Sci, 22:918-922.
Quisenberry, J.E., C .W. Wendt, J.D. Berlin and B.L. McMichel. 1985. Potential for Using leaf turgidity to select drought tolerance in cotton. Crop Sci, 25: 294-299.
Quisenberry, J.E., W.R. Jordan, B.A. Roark and D.W. Fryrear. 1981. Exotic cottons as genetic sources for drought resistance. Crop Sci. 21: 889-895.
Qayyum, S.M.; N.A. Chaudhary, A.H. Ansari; M.M.A. Baig and M.I. Memon. 1992. Correlation and regression analysis among yield and its economic characters in upland cotton (Gossypium hirsutum L). Pak. J. Agri., Agril. Engg., Vet. Sci. 8(1-2): 28-31.
Rahman, M.M., R. Sultana, R. Podder, A.T.M.T. Islam, M.K. Islam and M.S. Islam. 2006. Nature of gene action in barley (Hordeum vulgare). Asian J. Pl. Sci. 5(2): 170-173.
Rao, M.R.G., K.G. Hiremath and K. Virupakshappd. 1978. Correlation studies in upland cotton (Gossypium hirsutum L.). Mysore J. Agri. Sci. 2(1): 13-16. Rehman, A., M.A. Khan and I. Hassan. 1993. A diallel analysis of varietal different for some
ginning and fibre traits in Gossypium hirsutum L. Crosses. Pak. J. Agric. Res. 31(3): 257-266.
Rehaman, S., M.A. Khan and M.A. Khan. 1988. Genetic analysis of yield and yield components
in various crosses of American upland cotton. Sarhad J. Agri. 4(4): 495-5 14.
Rajeshwari, V.R. 1995. Evolution of cotton genotypes for drought tolerance under rain fed conditions. Ann. Pl. Physiol. 2: 109-112.
Ramalingam, A. and N. Sivasamy. 2002. Genetics and order effects of seed cotton yield in upland cotton (Gossypium hirsutum L.) triallel analysis. Indian. J. Genet. and Breed. 62 (4): 359-360.
Randhawa, A.S., S.K. Sharma and H.S. Dhaliwal. 1988. Screening for drought tolerance in wheat. Crop Improv. 15(1): 61-64.
Randhawa, L.S., G.S. Chahal, and T.H. Singh. 1986. Role of epistasis in the inheritance of yield and its components in upland cotton. Ind. J. Agric. Sci. 56(7): 494-496.
Rao, K.V.K. and T.N. Mary. 1996. Variability, correlation and path analysis of yield and fibre traits in upland cotton. J. Res. ANGRAU, 24(3/4): 66-70.
Rasheed, A., W. Malik, A.A. Khan, N. Murtaza, A. Qayyum and E. Noor. 2009. Genetic evaluation of fiber yield and yield components in fifteen cotton (gossypium hirsutum) genotypes. Int. J. Agric. Biol.,11(5):581-585.
167
Rauf S., T. M.Khan, H. A. Sadaqat and A. I. Khan. 2004. Correlation and path coefficient analysis of yield components in cotton (Gossypium hirsutum L.). Int. J. Agri. Biol. 6(4): 686–688.
Reddy, A.N. and A. Satyanarayana. 2005. Genetics of yield and fibre quality traits in American cotton (Gossypium hirsutum L.). Ann. Agric. Res. 26(2): 190-193.
Reddy, A.N. and S.R. Kumari. 2004. Genetic components of variation of physiological attributes for drought screening of genotypes in American cotton (Gossypium hirsutum L.). Ann. Agri. Res. 25(3): 412-414.
Rekika, D., G. Arnau, S. El-Taffari and P. Moneveum. 1995. Photosynthetic gas exchange parameters as predietive criteria for drought resistance in durum wheat and barley. In photosynthesis from light to biosphere volume IV. Proceeding of xth international photosynthesis congress, Montpellier, France, 20-25 August 1995. (WBT. Abst. 13(15): 4744; 1996).
Ritchie, S.W., H.T. Nguyen and A.S. Hholaday. 1990. Leaf water content and gas exchange parameters of two wheat genotypes differing in drought resistance. Crop Sci. 30: 105-111.
Saeed,F., T. Salam and M.Ikram.1996. geneaction in Interspecific hybrids of Grossypuim hirsutum L.for yield parameters.J. Agric. Res. 34(1):65-71.
Saghir, A., M.Z. Iqbal, A. Hussain, M.A. Sadiq and A. Jabbar. 2003. Gene action and heritability studies in cotton (Gossypium hirsutum L). Pak. J. Biol. Sci. 3(4): 443-450
Salahuddin, S.S. Abro,, M. M. Kandhro., L. Salahuddin and S. Laghari.2010. Correlation and Path Coefficient Analysis of Yield Components of Upland Cotton (Gossypium hirsutum L.) Sympodial. World Appl. Sci. J. 8 :71-75. Sangwan, R.S. and J.S. Yadava. 1987. Association analysis for some traits in Upland cotton
(Gossypium hirsutum L.) Ann. Agric. Res. 8(1): 156-158.
Sanyasi, I.S. 1981. Genetics of yield and its components in upland cotton. (Gussypium hirsutum L). Thesis Abst. Haryana Agric. Univ. Hissar, Ind. 7 (4): 336-337. (Pl. Br. Absts. 52(12): 10613: 1982.
Saranga, Y., I. Flash and D. Yakir . 1998. Variation in water use efficiency and its relation to carbon isotope ratio in cotton. Crop Sci., 38 (3): 782-787.
Saranga, Y., M. Menz, C. Jiang, R. Wright, D. Yakir and A.H. Paterson. 2001. Genomic dissection of genotype x environment adaptation conferring adaptation of cotton to arid conditions. Genome Res., 11: 1988-1995.
168
Saravanan, N.A., A. Gopalan and R. Sudhagar. 2003. Genetic analysis of quantitative characters in cotton (Gossypium spp.). Madras Agric. J. 90 (4-6): 236-238.
Saravanan, N.A., A. Gopalan. 2003. Combining ability for yield components in intra and inter specific hybrids of cotton (Gossypium spp.). Madras Agric. J. 90 (4-6): 239-242.
Saravanan, S., K. Koodalingam and T.S. Raveendran. 2006. Association analysis of some quantitative and qualitative traits in intraspecific crosses of desi cotton (Gossypium arboreum L.). Res. Crops, 7(2): 449-452.
Sarwar. G., M. Baber., N. Hussain., I. A. Khan., M. Naeem., M. A. ullah and A. A. Khan. (2011). Genetic dissection of yield and its components in upland cotton (Gossypium hirsutum L.). fr. J. Agric. Res. 6 (11): 2527-2531.
Satange, I.V., P.W. Khorgade, M.R. Wandhare, B.R. Patil and S.R. Golhar. 2000. Studies on genetic variability and correlation coefficient in American cotton. J. Soils Crops 10(1): 94-97.
Sayal, O.U and M.Z. Sulemani. 1996. Comparison of gene action controlling the qualitative traits in some early maturing cultivars of American cotton (Gossypium hirsutum L.) Sarhad J. Agri. 12(6): 653-661.
Schwendiman, J., S. Geobel and P. Kammachar. 1975. Use of path coefficient to determine yield
components in material derived from triple cotton hybrids (Gossypium hirsutum L. × Gossypium arboreum × Gossypium raimondii). Cotton fiber Tropics. 30(3): 277- 281.
Shah, S.A.H.; M.A. Khan; M.A. Khan and S. Ahmed. 1993. Diallele analysis for gene action and combining ability in cotton. Pak. J. Agri. Res. 14(2-3): 101-1 14. Shah, S.A.H. 1995. Path coeffiecient and correlation studies in upland cotton (G. hirsutum).
MSc. (Hons) Thesis, Deptt. Plant Breeding and Genetics, Uni. Agri. Faisalabad. Shahbaz, A. 2004. Genetic linkage studied for drought tolerant and agronomic traits in upland
cotton. M.Sc. Thesis, Deptt. Plant Breeding and Genetics, Uni. Agri. Faisalabad. Shi, W.J. 1998. Research on the correlation between earliness and agronomic characters of upland cotton in Xinjiang. China Cottons. 25(4): 17-18. Shakeel., A., I. A. Khan and F. M Azhar. 2001. Study pertaining to the estimation of gene
action controlling yield and related traits in upland cotton. Online J. Biol. Sci., 1(2):67-70.
169
Seki, M., M. Narusaka, J. Ishida, T. Nanjo, M. Fujita, Y. Oono, A. Kamiya, M. Nakajima, A. Enju, T. Sakurai, M. Satou, K. Akiyama, T. Taji, K. Yamaguchi-Shinozaki, P. Carninci, J. Kawai, Y. Hayashizaki, and K. Shinozaki. 2002. Monitoring the expression profiles of 7000 Arabidopsis genes under drought, cold and high-salinity stresses using a full-length cDNA microarray. Plant J., 31: 279–292.
Selote, D. S., Chopra, R. K. 2004. Drought-induced spikelet sterility is associated with an inefficient antioxidant defense in rice panicles. Physiologia Plantarum, 121, 462–471.
Siddique M.R.B., A. Hamid, and M.S. Islam. 1999. Drought stress effects on photosynthetic rate and leaf gas exchange of wheat. Bot. Bull. Acad. Sin.(1999) 40:141-145.
Siddique, M. H., F. C. Oad., U. A. Buriro. 2007. Rsponse of cotton cultivars to varying irrigation regimes. Asian J. Plant Sci. 6 (1): pp 153-157.
Silva, F.P.D.A. and J.F. Alves. 1983. Estimation of epistatic, additive and dominance variation in cotton (G. hirsutum L.) race latifolium Hutch. Revista Brasileria de Genetica (Brazil), 6(3): 491-503.
Singh, J., S. N. Bhardwaj and M. Singh. 1990. Leaf size and specific leaf weight in relation to its water potential and relative water content in upland cotton (Gossypium hirsutum L.). Ind. J. Agri. Sci. 60 (3): 215-216
Singh, M., T.H. Singh, G.S. Chahal and L.S. Randhawa. 1990. Genetic analysis of lint yield and its components in cotton. Crop Improve. 17(1): 64-67.
Singh, J.R.P. and B.S. Sandhu. 1985. Estimation of genetic variability for lint and seed characters in cotton (Gossypium hirsutum L.). J. Res. Punjab Agric. Univ. India. 22(4): 601-606.
Singh, P. and S.S. Narayanan. 1993. A brief review on breeding aspects of plant type in cotton. J.
Ind. Society Cotton Improv. 18 (1): 1-14.
Singh, P. and S.S. Narayanan. 2000. Biometrical Techniques in Plant breeding. Kalyani Publishers, New Delhi India: 70.
Singh, R.B., M.P. Gupta, and Dharampal. 1971. Genetics of certain yield characters in upland
cotton diallel analysis. J. Genet. 60(3): 24 1-249.
Singh, S.B., D. Singh and S.S. Narayanan. 1996. Variation in physio-morphological characters related to drought tolerance in cotton (Gossypium spp.). Ind. J. Agric. Sci. 66 (6): 357-359.
170
Singh, S.P. 1995. Selection for water stress tolerance in interracial populations of commen bean. Crop Sci., 35: 118-124.
Singh, T.H., M.A. Quader and G.S. Chahal. 1983. Estimation of gene effects for some quatitative characters in upland cotton. Cot. Fib. Trop. 38(4): 319-322.
Singh, P. and G.S. Chahal. 2005. Estimates of additive, dominance and epistatic variation for fibre quality characters in upland cotton (Gossypium hirsutum L.). J. Cotton Res. Development, 19(1): 17-20.
Singh, P., and H.G. Singh.1981. Gene action, heritability and genetic advance in upland cotton.
Ind. J. Agric. Sci. 51(4): 209-213.
Singh, R.B., M.P. Gupta, B.R. Mar and D.K. Jain. 1968. Variability and correlation studies in yield and quality characters in Gossypium hirsutum L. Ind. J. Genet. 28: 216-222.
Singh, V., C.K. Pallaghy and D. Singh. 2006. Phosphorus nutrition and tolerance of cotton to water stress II. Water relations, free and bound water and leaf expansion rate. Field Crops Research, 96 ( 2-3): 199-206.
Singh, D and J.P. Yadavendra. 2002. Genetic analysis of three quantitative characters in cotton. Indian. J. Genet. Pl. Breed. 62 (1): 85-86.
Sinha, S. K., in Approaches for Incorporating Drought and Salinity Resistance in Crop Plants (eds Chopra, V. L. and Paroda, R. S.), Oxford and IBH, New Delhi, 1986, pp. 56–86.
Soomro, B.A., M.H. Channa and M. Ahmad. 1982. Correlation studies in Gossypium hirsutum L. The Pak Cottons, 26(1): 39-5 1.
Steel, R. G. D. J. H. Torrie and D.A. Dickey. 1997. Principles and Procedures of statistics: Biometrical Approach. McGraw Hill Book Co., New York, USA.
Subhan, M., H.U. Khan and R. Ahmed, 2000. Comparison of the gene action controlling metric characters in upland cotton (Gossypium hirsutum L). Pak. J. Biol. Sci. 3(12): 2087 – 2090.
Subhani, G.M. and M.A. Chowdhry. 2000. Inheritance of yield and some other morpho-physiological plant attributes in bread wheat under irrigated and drought stress conditions. Pak. J. Biol. Sci. 3 (6): 983-987.
Sultan, M.K., B.N. Mitra, R. Choudhury, M.M. Kamruzzaman and M.A. Matin. 1999. Correlation and path analysis in upland cotton (Gossypium hirsutum L.). Bangladesh J. Sci. Indust. Res. 4(1): 55-58.
171
Tabassum, M. I. 2004. Genetics of physio-morphological traits in Zea mays L. under normal and water stress conditions. Ph.D. Thesis, Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan.
Tahir. M. H. N., M. Imran., and Medhet. 2002. Evaluation of Sunflower(Helianthus annuus L.) Inbred Lines for Drought Tolerance. Int. J. Agri. Biol., 4 (3 ):398-400.
Takele, A. 2000. Seedling emergence and of growth of sorghum genotypes under variable soil moisture deficit. Acta Agron. Hungarica. 48: 95-102. Tariq, M., M. A. Khan, T. Jamil and G. Idris. 1991. Indentification of parents for
hybridization through combining ability analysis in upland cotton. Sarhad J. Agric., 7(5): 633-641.
Taize and E. Zeiger. 1991. Plant physiology. The Benjamin Commings Publishing Co; Inc; California. Pp344-355.
Taiz, L. and E. Zeiger. 2006. Stress physiology. In: L. Taiz, and E. Zeiger, eds. Sinauer Associates. Plant Physiology, 4 th ed. Pp: 671-681. Tang, B., J.N. Jenkins, C.E. Watson, J.C. McCarty and R.G. Creech. 1996. Evaluation of
genetic variances, heritabilities, and correlations for yield and fiber traits among cotton F2 hybrid populations. Euphytica, 9 1(3): 315-322.
Tomar, S.K., S.P. Singh, and S.R.S. Tomar. 1992. Correlation and path coefficient analysis for yield components in desi cotton (Gossypium arboreum L.). Crop Res. Hisar, 5(7): 274-278.
Tripathy, J. N., J. Zhang, S. Robin, T. T. Nguyen and H. T. Nguyen. 2000. QTLs for cell-membrane stability mapped in rice (Oryza sativa L.) under drought stress. Theor. App. Genet., 100: 1197-1202.
Turner, N. C., Stress Physiology in Crop Plants (eds Mussell, H. and Staples, R. C.), Wiley, New York, 1979, pp. 343–372.
Turner, N.C. 1986. Crop water deficit: a decade of progress. Adv. Agron., 39: 1-51. Turner, N. C. 1986. Adaptation to water deficits: a changing perspective. Aust. J. Pl. Physiol. 13: 175-190.
Turner, N.C. 1997. Further progress in crop water relations. Adv. Agron., 58: 293-338.
Tyagi, A. P. 1987. Correlation studies on yield and fibre traits in upland cotton (Gossypium hirsutum L.). Theor. Appl. Genet. 74(2): 280-283.
172
Tyagi, A.P. 1988. Genetic architecture of yield and its components in upland cotton. Ind. J. Agri. Res. 22(2): 75-80.
Tyagi, A.P. 1994. Correlation coefficients and selection indices in upland cotton (Gossypium hirsutum L.). Ind. J. Agric. Res. 28(3): 189-196.
Ulloa, M. 2006. Heritability and correlations of agronomic and fibre traits in an okra leaf upland cotton population. Crop Sci. 46: 1508-1514.
Ullah. I., M. Rehman., M. Ashraf and Y. Zafar. 2008. Genotypic variation for drought tolerance in cotton (Gossypium hirsutum L.): Leaf gas exchange and productivity. Flora. 203: 105-115.
Vasal, S. K., H. Cordova, D. L. Beck and G. O. Edmeades. 1997. Choices among breeding procedures and strategies for developing stress tolerant maize germplasm. In: Edmeades, G.O., Bänziger, M., Mickelson, H.R., Pena-Valdiva, C.B. eds., Developing drought and low N tolerant maize.
Vurayai, R., V. Emongor and B. Moseki. 2011. Effect of water stress imposed at different growth and development stages on morphological traits and yield of Bambara groundnuts (Vigna subterranean L. Verdc ).
Vyahalkar, G.R., N.L. Bhale and L.A. Deshpande. 1984. Inheritance of fibre traits in
Gossypium arboreum L. Ind. J. Agric. Sci. 54(9): 702-704. Waldia, R.S., D.S. Jatasra and B.N. Dahiya. 1979. Correlation and Path analysis of yield
components in Gossypium arboreum L. Ind J. Agric. Sci. 49(1): 32-34.
Waqar-ul-haq, M. F. Malik, M. Rashid, M. Munir and Z. Akram. 2008. Evaluation and estimation of heritability and genetic advancement for yield related attributes in wheat lines. Pak. J. Bot. 40(4): 1699-1702.
Wang, X.D. and J.J. Pan. 1991. Genetic analysis of heterosis and inbreeding depression in upland cotton. Acta Agronomica Sinica, 17(1): 18-23.
Wang Z.Y. and J.X. Zhao. 1992. Selection and analysis of economic boll weight of cotton. China
Cottons, 1:10-11.
Warner, J.N. 1952. A method for estimating heritability. Agron. J. 44:427-30.
Weltzien, H. C. and J. P. Srivastava. 1981. Stress factors and Barley productivity and theire application in breeding strategies, ICARDA, Aleppo (Syria). In barley genetics , Fourth. Int. Barley Genetics Symposium, Edinburgh, Scotland, pp.351-369.
173
White, J.W., R.M. Cchoa, F.P. Ibarra and S.P. Singh. 1994. Inheritance of seed yield, maturity and seed weight of common bean (Phaseolus vulgaris) under semi arid rain fed condition. J. Agric. Sci., 122: 265-273.
Winter, S.R., J.T. Musick and K.B. Porter. 1988. Evaluation of screening techniques for breeding drought resistant winter wheat. Crop Sci. 28: 512-516.
Wyn Jones, R. G., R. Storey, R. A. Leigh, N. Ahmad and A. Pollard. 1977. A hypothesis on cytoplasmic osmoregulation. In: Marr, E., O. Ciferri, (Eds.), Regulation of Cell Membrane Activiities in plants. Elsevier/North-Holland Biomedical Press, amesterdam, Pp.121-136.
Xin, L.Y. and H.X. Ming. 1998. Research on the combining ability and inheritance of 12 economic characters in upland cotton. China Cottons, 25(3): 9-11.
Xue, S., P.H. Wang, D.Q. Xu and L.R. Li. 1992. Effects of water stress on co2 assimilation of two winter wheat cultivars with different drought resistance. Acta-Phytophysiologica-Sinica, 18 (1): 1-7.
Younas, F. J and Shalaby, A. W. 1997. Correlation and path coefficient analysis of yield and its components in zero branching and normal branching types of Egyptian cotton Gssypium barbadense L. Annals. Agri. Sci. Mosh. 1997;35(3):1123-1134.
Zhang, J. F., Y. Lu., H. Adragna and E. Hughs. 2005. Genetic Improvement of New Mexico Acala Cotton Germplasm and Their Genetic Diversity. Crop Sci. 45:2363–2373
Zhou, Q.H. 1994. Genetic analysis of yield components and fibre quality characters in glandless
Zia-Ul-Islam, H.A. Sadaqat. and F.A. Khan. 2001b.Combining ability of some hirsute cotton types for economic traits. International Journal of Agriculture and Biology, 3(4): 411-412.
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Appendix 1. Comparison of Means for shoot length and root length under normal and drought
Means sharing similar letters are statistically non-significant (P>0.05) by Duncan’s New Multiple Range test
S # Genotypes Shoot Length Root Length Normal Drought Normal Drought