Determination of Genetic Variation for Earliness, Yield and Fiber Traits in Advance Lines of Cotton (Gossypium hirsutum)

Volume06-2018
Advances in Agricultural Science 06 (2018), 02: 59-74

Determination of Genetic Variation for Earliness, Yield and Fiber Traits in Advance Lines of Cotton (Gossypium hirsutum)

Jehanzeb Farooq 1, Muhammad Rizwan 1, Sadaf Saleem 1, Iram Sharif 1, Shahid Munir Chohan 2, Muhamma Riaz 2, Farrukh Ilhai 1 and Riaz Ahmad Kainth3

Research Officer, Cotton Research Station, Faisalabad, Pakistan.
Assistant Botanist, Cotton Research Station, Faisalabad, Pakistan.
Botanist, Cotton Research Station, Faisalabad, Pakistan.

ABSTRACT

The genetic components, genetic variability, correlation and path analysis between yield, fiber quality and earliness traits were evaluated in 18 advance lines of cotton along with two checks. The values of heritability were higher for yield and quality parameters, but for earliness traits heritability was moderate. The results of correlation coefficients for days to flower initiation, boll weight, GOT%, sympodia branches and boll number per plant showed significant positive genotypic and phenotypic associations with seed cotton yield. Maximum values of direct effects on yield were also observed for these traits. The results of principal component analysis revealed that 4 four components contributed 78% of total variation. Cluster analysis showed that genotypes in cluster-II viz: FH-488, FH-490, FH-142, FH-451, FH-452, FH-453, FH-455 are exploitable not only for hybridization purpose but also some of the genotypes in this cluster may be recommended for testing in national and provincial trials.

Keywords: Breeding, Fiber quality, Genetic diversity, Path analysis, Cotton


How to Cite: Farooq, J., Rizwan, M., Saleem, S., Sharif, I., Munir Chohan, S., Riaz, M., Ilhae, F., & Ahmad Kainth, R. (2018). Determination of Genetic Variation for Earliness, Yield and Fiber Traits in Advance Lines of Cotton (Gossypium hirsutum). Advances in Agricultural Science, 6(2), 59-74. 

Introduction

Pakistan is the fourth largest producer of seed cotton worldwide. Crop improvement for enhanced lint production in upland cotton had been a priority of cotton breeders for centuries. Fiber yield is a complex trait and inherited quantitatively; thus, strongly influenced by environmental conditions (Percy et al., 2006; Ragsdale and Smith, 2007; Khan et al., 2009). Correlation coefficients provide a good general estimate of association in independent characters and degree of their linear relationship (Ali et al., 2009). It gives a good index of corresponding change in one trait at the proportionate expense of the other trait (Ahmad et al., 2008; Khan et al., 2007). Different plant attributes possess a significant positive or negative correlation with fiber yield and quality traits in cotton. Sympodia per plant and bolls per plant showed positive correlation with seed cotton yield (Salahuddin et al., 2010; Khan and Hassan, 2011) while days to 50% flowering, micronaire value and uniformity ratio correlated negatively (Srinivas et al., 2015). Estimation of correlation associations among different traits is helpful for breeders to evaluate selection criteria and simultaneous selection for yield and quality traits (Farooq et al., 2013). However, correlation coefficients are insufficient to describe the causal effects of different characters, path analysis is needed to divide the correlation coefficients into its components and determine the direct and indirect effects of different causal components on yield (Yücel et al., 2006; Kale et al., 2007; Ali et al., 2009). Boll weight and number of bolls plant-1 depicted maximum positive direct effect on seed cotton yield (Srinivas et al., 2015). Utilization of available diversity with respect to morphological traits is essential to initiate a well-planned breeding programme (Zada et al., 2013). The exploitation of genetic differences in cotton for quality and yield parameters has been observed by many researchers (Farooq et al., 2014). Shazia et al. 2010 suggested that selection criteria based on yield components like bolls per plant, sympodial branches, ginning out turn and boll weight could be used for the development of superior cotton genotypes. For assessing diversity and finding superior genotypes, principal component analysis is the most exploited statistical tool as aids breeders in identifying the major contributor to total variability at each axis of variability (Rehman et al., 2015, Sharma, 2006). The objective of this study was to find out genotypic and phenotypic correlation among different characters along their direct and indirect effects on seed cotton yield. Furthermore, assessment of genetic diversity may assist in identification of high yielding, early maturing genotypes with improved fiber quality. The superior genotypes could be used directly in breeding program or may be further evaluated in provincial and national testing.

 

Materials and Methods

Genotypes and site characteristics

Eighteen genotypes along with two check varieties were planted on 1 May 2016 for preliminary yield testing during crop season 2016-2017 at experimental area of Cotton Research Station, Faisalabad, Punjab, Pakistan which is present at an altitude of 184 m at 31° 21′ 52″ N 72° 59′ 40″ E with average rainfall of 300 mm.

 

Experimental design

Genotypes were arranged in a randomized complete block design with three replications. Each treatment was planted in a plot size measuring 4.57 × 3.05 m, with rows spaced at 75 cm apart. Distance between plants within rows was 30 cm. Management practices including weeding, hoeing, irrigation, fertilization and plant protection measures was, done according to the needs of the crop.

 

Measurement of traits

Ten true to type plants were selected from the center two rows of each experimental plot and tagged for identification. Days to first square and flower were counted from sowing time till the first square and flower appear. Nodes to first fruiting branches were counted from zero node to the node at which first flower appeared. The monopodial branches were counted at maturity in tagged plants. Boll number and sympodial branches were counted from each tagged plant. The height of selected plants was measured in centimeters from the bottom to the top of the plant at maturity. For estimating average boll weight, 25 bolls were collected from base, top and middle of each selected plant (Farooq et al., 2017). For measuring seed cotton yield, seed cotton was harvested at two time intervals with the first harvest initiated 120 days after planting and the second harvest conducted after 150 days of planting. The seed cotton was then combined for evaluation. Clean dry seed cotton samples were weighed and ginned with roller ginning machine (HT-ZHJ20). The lint was weighed to calculate ginning turnout (GOT %) using the formula: GOT (%) = lint weight / total weight of seed cotton × 100. Fiber length, strength and fineness were measured using USTER® HVI-1000.

 

Figure 1. Mean performance of 20 cotton genotypes with respect to days to squaring and nodes to 1st fruiting branch

 

 

Statistical analysis

Data analysis utilized MSTAT-C package (Russell, D. Freed, Michigan State University, USA, 1984). Broad sense heritability was measured following the procedure of Burton and De Vane (1953). The correlations were measured using the formula described by Kwon and Torrie (1964). The genotypic correlations were calculated by adopting the method of Lotherop et al., (1985). The T-test was utilized to test the significance of phenotypic correlations as prescribed by Steel and Torrie (1984). Path analysis was as described by Dewey and Lu (1959).

Figure 2. Mean performance of 20 cotton genotypes for bolls per plant and sympodia per plant

 

Treatment means were subjected to statistical and PCA analysis using software packages of Minitab version 17 and STATISTICA version 8.1 (Sneath & Sokal 1973). To analysis the pattern of variation and for the calculation of association between traits, the first two principal components were plotted against each other. Cluster analysis was performed using K-means clustering and tree diagram based on elucidation distances as developed by Ward’s method using SPSS version 22.

 

Results and Discussions

Genetic Components

The data for 13 traits showed significant variation across the 20 genotypes (Table 1). The estimates of phenotypic coefficient of variation (PCV) were higher than genotypic variation (GCV) for all traits.

Figure 3. Mean performance of 20 cotton genotypes with respect to staple length and strength

Similar results were reported by Farooq et al., (2013) and Mendez-Natera et al., (2012). Heritability (broad sense) estimates were maximum for fiber quality traits. For yield contributing traits, the heritability magnitude was highest for bolls per plant followed by boll weight, and sympodial branches. For earliness related traits, the magnitude was moderate. Higher estimates of extent of transmitted variation were reported by Farooq et al., 2013 for fiber, earliness and yield related parameters. Lower estimates of heritability for bolls per plant and seed cotton yield and higher values for fiber traits have been reported by Basbag and Gencer (2004). Moderate estimates for plant height, fiber length and strength and lower values for boll weight, boll number and yield were reported by Mendez-Natera et al., (2012). Selection on the basis of yield and fiber quality traits having higher estimates would be beneficial. Higher estimates of heritability are not only useful in predicting gain under selection but also indicative of additive gene effects. The contradiction of results reported by

Table 1. Mean square and genetic component estimates for earliness, yield and fiber quality traits in cotton

Characters1 Mean squares GCV (%) PCV (%) (Heritability *)
DFS 7.20** 3.99 4.93 66
DFF 8.10** 2.68 3.38 63
PH (cm) 516.07** 9.71 9.96 95
SPP 22.9 11.59 12.05 93
MPP 1.61** 21.20 25.11 71
BPP 74.43** 13.28 13.63 95
NFFB 1.65** 8.25 10.76 59
BW (g) 0.29** 7.72 7.93 95
GOT (%) 5.48** 2.97 3.39 77
SL(mm) 6.07** 5.10 5.13 99
SF (ug/inch) 0.37** 6.93 6.98 99
SS (g/tex) 0.14** 9.07 9.10 99
Yield (kg/ha) 272702** 8.26 8.60 92

1DFS=days to first square, 2DFF= days to first flower, 3PH= plant height, 4SPP= sympodia per plant 5MPP= monopodia per plant, 6BPP= bolls per plant, 7NFFB= nodes to first fruiting branch 8BW= boll weight, 9GOT%= ginning out turn (%), 10SL= staple length 11SF= staple fineness 12SS= staple strength. *Significant at α = 5%, **significant at α = 1%

 

Figure 4. Biplot between PC-1 and 2 showing contribution of earliness, yield and quality traits in variation

many scientists is mainly due to the variations in location, environment and genotypes exploited in the experiments. The mean performance of 20 cotton genotypes for days to squaring, nodes to fruiting branch, bolls per plant, sympodia per plant, staple length and strength is presented in Fig-1, 2 and 3 respectively, the results reveled that genotype FH-453 carried maximum sympodia and bolls per plant and produced maximum yield while in term of earliness, FH-313 and FH-489 completed their life cycle earlier thus characterized as early maturing lines. In fiber quality parameters, FH-490, FH-404, FH-453 and FH-454 produced staple length >29.50 mm while maximum fiber strength of >33 g/tex was observed in genotypes FH-313 and FH-334.

 

Genotypic and Phenotypic Correlations

The results of correlation coefficients indicated days to first flower, sympodia per plant, bolls per plant, boll weight and GOT showed highly significant positive genotypic and phenotypic association with yield and were major yield contributing traits (Table 2). These results were in accordance with previous reports (Ashokkumar and Ravikesavan 2010; Farooq et al., 2014). However, the values of phenotypic correlation for these traits were highly significant as compared to genotypic values, the reason may be the positive buffering effects of environmental conditions in crop growing season.

According to Farooq et al., (2013), days to first square had positive genotypic correlation with days to first flower and monopodia per plant. Positive association of days to first square with days to first flower at genotypic and phenotypic levels were observed in the present study, but monopodia per plant showed no significant correlation. Days to first flower showed positive association with sympodia per plant at the genotypic and phenotypic level, but non-significant correlation observed for monpodial branches per plant. These findings deviated from results reported by Farooq et al., (2013). Days to first flower showed positive correlation with plant height at genotypic level. Days to first flower also showed a positive genotypic and phenotypic correlation with bolls per plant, which indicate early flowering genotypes produce more bolls per plant. For fiber quality parameters, days to first flower negatively correlated with the fiber fineness and strength at genotypic and phenotypic levels; whereas, fiber length showed no significant association. Ahuja et al., (2006) reported a significant positive association between plant height and seed cotton yield, but the results of the present study indicate the existence of a significant negative genotypic correlation. Plant height showed a significant negative correlation with monopodia per plant.

Monopodia per plant showed no significant association with nodes to first fruiting branch, GOT % and with most fiber traits. According to Ahmad et al., (2008) monopodia per plant negatively correlated with yield, but the results of the present study indicated that the monopodia per plant had a significant positive correlation with bolls per plant and yield at both genotypic and phenotypic levels. The positive association of monopodia per plant with yield was in agreement with results reported by Ahuja et al., (2006). Boll weight showed positive correlation at genotypic level and a highly significant positive association at the phenotypic level.

Sympodia per plant showed significant positive genotypic association with bolls per plant, boll weight, GOT % and yield, and highly significant phenotypic correlation for these traits.  Positive correlation with fiber quality related attributes except with fiber strength were also observed. Sympodia per plant showed no significant positive association with monopodia per plant, fiber length and fiber fineness, but showed a significant negative genotypic correlation with fiber strength. The positive association of sympodia per plant with yield was also reported by Ahmad et al., (2008), Farooq et al., (2014) and Khan et al., (2017). These results suggest an increase in the number of sympodia per plant have more positive contribution to yield as compared to monopodia per plant. Number of bolls

Table 2. Genotypic and phenotypic Correlation coefficient of various yield, fiber and earliness traits in 20

 

 

DSS DFF PH (cm) SPP MPP BPP NFFB BW (g) GOT (%) SL (mm) SF (µg/inch) SS (g/tex) Yield (kg/ha)
DSS G 1.0000 1.0244* 0.0908* -0.0926 0.1267 0.1619* 0.8227* 0.2437 0.1275 -0.1616 -0.4934* -0.4322* -0.0002
P 1.0000 0.6156** 0.0590 -0.0681 -0.0129 0.1239 0.4467** 0.1805 0.0809 -0.1238 -0.4218** -0.3452** 0.0215
DFF G 1.0000 0.1226* 0.6786* -0.012 0.3799* 0.4188* 0.3772 0.3400* -0.205 -0.4205* -0.5334* 0.5892*
P 1.0000 0.1055 0.5241** 0.0486 0.2728* 0.2588* 0.2325* 0.1892 -0.1549 -0.3375** -0.4231** 0.4735**
PH (cm) G 1.0000 0.0137 -0.5874* 0.3099* -0.0775 -0.084 0.1921* 0.5793* -0.4673* 0.3019* -0.1182*
P 1.0000 0.0341 -0.4571** 0.3025* -0.0859 -0.0904 0.1500 0.5646** -0.4531** 0.2888* -0.0986
SPP G 1.0000 0.1707 0.5841* 0.2912* 0.5145* 0.7051* 0.0544 -0.1001 -0.1851* 1.0009*
P 1.0000 0.1474 0.5628** 0.1848 0.4794** 0.5973** 0.0497 -0.1025 -0.1772 0.9320**
MPP G 1.0000 0.3722* -0.0287 0.7780* 0.0872 0.0141 -0.1506 0.2268* 0.3498*
P 1.0000 0.2869* 0.0484 0.6359** 0.1419 0.0140 -0.1206 0.1808 0.2666*
BPP G 1.0000 0.2407* 0.8492* 0.7154* 0.3680* -0.4609* 0.1205* 0.6971*
P 1.0000 0.1734 0.7963** 0.5939** 0.3516** -0.4429** 0.1182 0.6556**
NFFB G 1.0000 0.5238 0.6256* -0.3345* -0.4271 -0.5304* 0.4079*
P 1.0000 0.3278* 0.4428** -0.242 -0.3117* -0.4017 0.2792*
BW (g) G 1.0000 0.4990* 0.2236 -0.3834 0.0607 0.6931*
P 1.0000 0.4528** 0.2074 -0.3686** 0.0569 0.6479**
GOT (%) G 1.0000 -0.0169 -0.2476 -0.2201* 0.7464*
P 1.0000 -0.0162 -0.2153 -0.2008 0.6159**
SL (mm) G 1.0000 -0.2186 0.5341* 0.0162*
P 1.0000 -0.2174 0.5259** 0.0192
SF(µg/inch) G 1.0000 0.1927 -0.1450*
P 1.0000 0.1919 -0.1483
SS (g/tex) G 1.0000 -0.1298*
P 1.0000 -0.1282
Yield (kg) G 1.0000
P 1.0000

1DFS=days to first square, 2DFF= days to first flower, 3PH= plant height, 4SPP= sympodia per plant 5MPP= monopodia per plant, 6BPP= bolls per plant, 7NFFB= nodes to first fruiting branch 8BW= boll weight, 9GOT%= ginning out turn (%), 10SL= staple length 11SF= staple fineness 12SS= staple strength. *Significant at α = 5%, **significant at α = 1%

 

per plant showed a significant positive genotypic correlation with boll weight and a highly significant positive phenotypic association. This was in agreement with previous results reported by Khan and Hassan (2011).

For fiber quality, days to flowering had non-significant negative correlation with fiber length, but negatively correlated with the fiber fineness and strength as early maturity does not provide sufficient time for secondary accumulation of cellulose which improves the strength. So early maturing genotypes usually suffers from lower fibre strength. Fiber strength also showed a negative correlation with GOT %. Maximum fiber length can be achieved along with good fiber strength through simultaneous selection for both traits, because there exists a significant positive genotypic correlation between these traits. Among fiber quality parameters, fiber strength and fiber fineness exhibited significant negative genotypic correlation with seed cotton yield. Khan et al. (2017) reported a significant negative correlation between fiber strength and micronaire. Iqbal et al., (2006) reported negative effects of GOT % and fiber length on seed cotton yield, but present results indicated the positive genotypic correlation of fiber length with yield along with its highly significant positive association with fiber strength at phenotypic level. GOT % had a significant negative association with fiber strength at genotypic level. While in case of yield, GOT% showed a significant positive correlation with it at genotypic level and highly significant positive association at phenotypic level.

 

Path Co-efficient Analysis

The results of this study in the form of direct and indirect effects of different traits on yield have been presented in table (3). Days to first square had positive direct effect on yield, which is indirectly contributed by bolls per plant, node to first fruiting branch and fiber fineness while it has negative influence on yield via indirect negative effects of days to first flower, plant height, sympodial and monopodial branches, boll weight, GOT, fiber length and strength. Farooq et al., 2014) reported positive direct effect of days to first square on seed cotton yield. Days to first flower had negative direct effect on seed cotton yield but made positive contribution in yield through days to first square, sympodia branches, monopodia branches, number of bolls, node to first fruiting branch and fiber fineness. The results are supported by Angadi et al., (2016) who reported negative direct effect of days to 50% flowering on seed cotton yield. Farooq et al., 2014 also reported negative direct effect of days to first flower on seed cotton yield. This suggests that development of early maturing genotypes will improve the yield potential.

Plant height has the highest negative direct effect on seed cotton yield but showed positive influence on seed cotton yield via day to first square, number of sympodia and monopodia branches, bolls per plant, boll weight, fiber length, fineness and strength. Negative association of days to first flower and node to first fruiting branch with plant height suggests that these two traits could not only be used indirectly for reducing plant height but also for development of high yielding early maturing genotypes. The results are supported by Angadi et al., (2016) who reported negative direct effect of plant height on seed cotton yield.

Sympodia branches per plant showed positive direct effect on cotton seed yield suggesting that selection could improve seed cotton yield. Indirect selection to increase the number of sympodial branches could be made via number of bolls per plant, node to first fruiting branch, fiber length and fineness, which have positive indirect effect on seed cotton yield. Negative indirect effects were observed for days to first square, days to first flower, plant height, monopodial branches, boll weight, GOT% and fiber strength. Farooq et al., (2014) reported positive direct effect of sympodia per plant on seed cotton yield and indirect positive effects were contributed via nodes to first fruiting branch, monopodia per plant, plant height, boll weight, fiber strength, and GOT%. Monopodia branches per plant has negative

 

Figure 5. Score plot between PC-1 and 2 showing contribution of different parameters in variability among 20 cotton genotypes.

 

 

Figure 6. Dendrogram showing the clustering of 20 cotton genotypes

 

direct effect, but showed positive indirect effects on seed cotton yield through days to first square, days to first flower, plant height, sympodia per plant, bolls per plant, and fiber length, strength and fineness. Iqbal et al., (2003) observed negative direct effect of monopodia branches. Negative indirect effects were produced by node to first fruiting branch, boll weight and GOT%. Plant height and number of bolls contributed maximum positive indirect effects. These findings are contradictory to the results of Alkuddsi et al., (2013) who reported high positive direct effect of monopodia per plant on seed cotton yield.

Number of bolls exerted maximum positive direct effect on seed cotton yield similar to results reported by Ahuja et al., (2006). The positive indirect effects were produced by days to first square, sympodia branches/plant, node to first fruiting branch, and fiber length, strength, and fineness. Negative indirect effects were created by days to first fruiting branch, plant height, monopodia branches and boll weight and GOT%. Sympodia branches/plant contributed maximum indirect positive effect, which suggests that more branches will contribute to a greater number of bolls. The results showed that this is highly effective trait for yield improvement. Similar results were reported by Iqbal et al., (2006) and Iqbal et al., (2003).

Node to first fruiting branch has positive direct effect on yield. The positive indirect effects were caused days to first square, plant height, sympodia and monopodia braches/plant, number of bolls and fiber fineness while days to first flower, boll weight, GOT%, fiber length and strength have negative indirect effect. Iqbal et al., (2006) reported positive direct effects of node to first fruiting branch on seed cotton yield. These results suggest that selection for node to first fruiting branch may aid in identification of early maturing and high yielding lines. Boll weight imparted significant negative direct effect on seed cotton yield while positive indirect effects were contributed via days to first square, plant height, sympodia per plant, bolls per plant, nodes to first fruiting branch, fiber length, strength and fineness. The negative impact of boll weight on yield was compensated via maximum indirect positive effect of bolls per plant. However, these findings are contradictory to the results of Alkuddsi et al., (2013) who reported high positive direct effect of boll weight on seed cotton yield. These findings suggest that this character could not be used for selection to improve yield.

GOT exerted negative indirect effect on seed cotton yield. Indirect positive effects were contributed via days to first square, sympodial branches, bolls per plant, node to first fruiting branch and fiber fineness. Number of bolls per plant has maximum positive indirect effect on GOT. Negative indirect effects were created via days to first fruiting flower, plant height, monopodia branches/plant, boll weight, fiber length and strength. Highest positive indirect effect of boll per plant suggests that GOT could be improved indirectly via selecting for boll number. Another study reported negative direct effect of GOT on yield and suggested its improvement via number of bolls (Iqbal et al., 2006).

In this study quality parameters did not show negative impact on overall yield except fiber fineness. Fiber length contributed by indirect positive effects of days to first flower, sympodial branches, number of bolls, GOT, and fiber fineness and strength. Maximum negative indirect effect was exerted by bolls per plant for fiber fineness. For fiber strength positive indirect effects were produced via days to first flower, bolls per plant, GOT and fiber length. Khan et al., (2014) and Rasheed et al., (2009) reported positive direct effect of fiber strength on yield.

 

Principal component and Cluster analysis

Principal component analysis revealed that four components showed eigen value more than unity and contributed 78.1% to the total variation (Table 4). The results of principal component analysis based on individual traits revealed that bolls per plant, boll weight, sympodia per plant and yield had

Table 3. Direct (diagonal) & Indirect (off-diagonal) effects of earliness, yield and fiber traits in cotton

DFS DFF PH (cm) SPP MPP BPP NFFB BW (g) GOT (%) SL (mm) SF (ug/inch) SS

g/tex)

Genetic correlation with yield
DFS 0.5874 -0.0964 -0.7906 -0.1915 -0.6241 1.1217 2.0267 -1.2701 -0.3060 -0.2411 1.6285 -1.8447 -0.0002
DFF 0.6017 -0.0941 -1.0673 1.4031 0.0590 2.6322 1.0318 -1.9659 -0.8162 -0.3059 1.3879 -2.2771 0.5892
PH(cm) 0.0533 -0.0115 -8.7092 0.0283 2.8932 2.1469 -0.1910 0.4377 -0.4611 0.8643 1.5424 1.2888 -0.1182
SPP -0.0544 -0.0638 -0.1191 2.0676 -0.8409 4.0469 0.7173 -2.6814 -1.6924 0.0811 0.3303 -0.7901 1.0009
MPP 0.0744 0.0011 5.1161 0.3530 -4.9251 2.5789 -0.0706 -4.0548 -0.2093 0.0210 0.4971 0.9680 0.3498
BPP 0.0951 -0.0357 -2.6988 1.2077 -1.8333 6.9282 0.5929 -4.4262 -1.7171 0.5490 1.5211 0.5143 0.6971
NFFB 0.4832 -0.0394 0.6752 0.6020 0.1412 1.6675 2.4635 -2.7302 -1.5016 -0.4991 1.4097 -2.2642 0.4080
BW (g) 0.1431 -0.0355 0.7313 1.0637 -3.8317 5.8836 1.2904 -5.2120 -1.1978 0.3336 1.2652 0.2591 0.6931
GOT (%) 0.0749 -0.0320 -1.6731 1.4578 -0.4295 4.9562 1.5411 -2.6009 -2.4003 -0.0251 0.8172 -0.9397 0.7464
SL(mm) -0.0949 0.0193 -5.0449 0.1124 -0.0694 2.5493 -0.8241 -1.1655 0.0404 1.4921 0.7216 2.2799 0.0162
SF (ug/inch) -0.2898 0.0396 4.0702 -0.2069 0.7419 -3.1932 -1.0523 1.9980 0.5944 -0.3262 -3.3003 0.7797 -0.1450
SS (g/tex) -0.2538 0.0502 -2.6294 -0.3827 -1.1168 0.8346 -1.3067 -0.3163 0.5284 0.7969 -0.6028 4.2687 -0.1298

1DFS=days to first square, 2DFF= days to first flower, 3PH= plant height, 4SPP= sympodia per plant 5MPP= monopodia per plant, 6BPP= bolls per plant, 7NFFB= nodes to first fruiting branch 8BW= boll weight, 9GOT%= ginning out turn (%), 10SL= staple length 11SF= staple fineness 12SS= staple strength

Table 4. Principle component analysis of earliness  yield and quality traits in 20 cotton genotypes

Variable PC-I PC-II PC-III PC-IV

Eigen value
4.346 2.432 1.983 1.388
Proportion 33.400 18.700 15.300 10.700
Cumulative 33.400 52.100 67.400 78.100
Factor loadings of 1st 4 principle components
Days to 1st square 0.164 -0.306 0.381 0.330
Days to 1st flower 0.289 -0.253 0.209 -0.060
Plant height (cm) 0.044 0.331 0.547 -0.218
Sympodia per plant 0.374 0.037 -0.168 -0.420
Monopodia per plant 0.175 0.081 -0.396 0.550
Bolls per plant 0.390 0.272 0.028 0.035
Nodes to 1st fruiting branch 0.237 -0.302 0.111 0.123
Boll weight (g) 0.388 0.145 -0.167 0.328
Ginning Out Turn % 0.347 0.013 -0.047 -0.245
Staple length (mm) 0.041 0.520 0.213 0.061
Staple Fineness (µg/inch) -0.239 -0.039 -0.426 -0.290
Staple strength (g/tex) -0.111 0.515 -0.083 0.149
Yield (kg/ha) 0.409 0.030 -0.222 -0.260

 

 

Table 5. Cluster means of earliness, yield and quality traits in 20 cotton genotypes

Variable Cluster-1 Cluster-II Cluster-III
Days to 1st square 31.13 31.71 31.53
Days to 1st flower 48.13 49.57 48.27
Plant height (cm) 127.17 132.71 137.40
Sympodia per plant 22.38 25.57 20.13
Monopodia per plant 3.00 3.14 2.47
Bolls per plant 35.17 40.81 32.73
Nodes to 1st fruiting branch 6.92 7.05 6.67
Boll weight (g) 3.85 4.18 3.61
Ginning Out Turn % 40.41 40.36 38.49
Staple length (mm) 27.10 28.28 28.01
Staple Fineness (µg/inch) 5.01 4.88 5.19
Staple strength (g/tex) 27.52 29.26 29.65
Yield (kg/ha) 3465.33 3824.33 3130.74
Name of genotypes  FH-489, FH-313, FH-407, FH-404, FH-456, FH-457, FH-458, MNH-886 FH-488, FH-490, FH-142, FH-451, FH-452, FH-453, FH-455 FH-334, FH-315, FH-450, FH-342, FH-454

 

maximum positive loadings on PC-1, while fiber fineness and strength had negative loadings. Fiber length and strength showed maximum positive loadings followed by plant height and bolls per plant on PC-2. Maximum positive loading on PC III were shown by plant height and days to squaring and flowering. Maximum positive values for PC-4 were shown by monopodia per plant, days to square and boll weight. A biplot of first two principal components showed the major contribution of bolls and sympodia per plant, GOT and boll weight (Fig-4). The score plot also confirmed the variation in the genotypes with FH-453, FH-488, FH-404, FH-455and FH-457 showing good yield potential with more bolls per plant, greater boll weights, more sympodia per plant and an increased GOT (Fig-5). Saeed et al., (2014) and Farooq et al., (2017) reported similar results while studying large number of cotton genotypes. The dendrogram of these genotypes is presented in Fig-6. Genotypes in cluster-II showed excellent results with more bolls per plant, higher boll weights, greater fiber length and yield with good GOT (Table 5). In other clusters showed some promising features but further single plant selection in these genotypes with respect to fiber quality is recommended.

 

Conclusion

The higher estimates of heritability and genetic advance in major yield related traits are indicative of presence of additive genetic effects. Therefore, early generation selection is recommended. Components of yield and some earliness traits showed strong positive and significant associations with yield thus may be exploited as selection criteria to increase seed cotton yield. Principal component analysis showed the major role of first 2 components in total variability and cluster analysis helped in the identification of superior genotypes for further utilization in hybridization programme and future evaluation in multi-locational yield testing.

 

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