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CORRELATION AND PATH COEFFICIENT ANALYSIS OF EARLINESS FIBER QUALITY AND YIELD CONTRIBUTING TRAITS IN COTTON (Gossypium hirsutum L.).

Byline: J. Farooq M. Anwar M. Riaz A. Farooq A. Mahmood M. T. H. Shahid M. Rafiq S. and F. Ilahi

ABSTRACT

The present investigations were designed to determine genotypic phenotypic correlation coefficients and path analysis between seed cotton yield earliness fiber and yield contributing traits in 53 cotton cultivars. Heritability and genetic advance was computed to determine the selection procedure for the material studied. Maximum value of GCV% and PCV % was observed in CLCuV% and seed cotton yield. Maximum broad sense heritability was found in traits like FS (99%) followed by BW (98%) GOT% (97%) and FF (96%). Moderate estimates of heritability were found for nodes to1st fruiting branch (35%) monopodia per plant (34%) and sympodia per plant (43%). Regarding correlation studies seed cotton yield have positive genotypic correlation with bolls per plant plant height boll weight staple length and strength earliness index and GOT%. Path coefficient analysis results revealed that the traits like earliness index% showed maximum positive direct effect on yield (0.63) followed by days taken to 1st square (0.17) GOT% (0.16) plant height (0.15) boll weight (0.15) and sympodia per plant (0.11). The traits like EI% and boll weight showed positive correlation higher heritability estimates and positive direct effect on yield thus may be used as selection criteria to increase yield.

Key words: Heritability Genetic Advance genotypic correlations path analysis cultivars seed cotton yield Cotton

List of abbreviations used: NTFFB= Nodes to 1st fruiting branch MPP= Monopodia per plant SPP= sympodia per plant PH= Plant height BWT= boll weight SL= Staple length FF= fiber fineness FS= Fiber strength EI= earliness index GOT= Ginning out turn DFS= days to 1st square DFF= days to 1st flower CLCuV= Cotton leaf curl virus GCV= genotypic coefficient of variation PCV= phenotypic coefficient of variation

INTRODUCTION

Cotton plays a vital role in boosting our national economy being the principle source of earning foreign exchange therefore it is considered to be the backbone of the economy of Pakistan. It is termed as white gold due to its importance as cash and industrial crop. Alongside fiber it also produces edible oil and cotton seed cake for human and animal consumption respectively.

The development of varieties having tolerance to CLCuV possessing better fiber quality and greater yield potential are the primary objectives of a cotton breeder. Seed cotton yield is influenced by both genetic and environmental factors. Interaction between these two factors makes the selection difficult. Knowledge about the relationship between yield and its components facilitates the breeders in the selection of desirable genotypes.The correlation analysis provides a good index to predict the corresponding change which occurs in one trait at the expanse of the proportionate change in the other (Khan et al. 2007; Ahmad et al. 2008). Taohua and Haipeng (2006) and Meena et al. (2007) studied the adaptability and stability of Gossypium hirsutum varieties and observed diverse values for different agronomic morphological and yield related traits. Iqbal et al. 2003 and Wang et al. 2004 found genetic variation and positive correlation for seed cotton yield and yield components in Gossypium hirsutum. Performance and positive association of seed cotton yield with yield components was observed in hirsutum cultivars (Mendez-Natera et al. 2012). Khan et al. (1999) and Khan (2003) found high genetic variability for yield and yield components in cotton. Khan et al. (2000) studied the earliness and agronomic traits of upland cotton cultivars using correlation analysis and found that monopodia had a negative direct effect on yield. Jost and Cothren (2000) and Badr (2003) also studied earliness and other yield contributing traits in different cotton cultivars and observed varied performance. DeGui et al. (2003) studied yield and yield components and found that the higher yield in cotton cultivars was mainly due to more number of bolls per plant. For a simultaneous selection of both yield and fiber quality traits knowledge about association of yield and fiber quality traits is a prerequisite. The present study was designed to explore the genetic potential of different cotton cultivars and relationship of seed cotton yield with different earliness fiber and yield related traits. MATERIALS AND METHODS

Plant Material and Site Characteristics: A total of 53 genotypes were evaluated at experimental area of Cotton Research Institute Faisalabad during the year 2011-12. Experiment was laid following a randomized complete block design (RCBD) with three replications. Each entry/treatment was a plot of 4.572 m A- 6.096 m size comprising 75 cm apart six rows. Distance between plants within rows was 30 cm. Normal agronomic and cultural practices (irrigation weeding hoeing and fertilizer applications) were adopted uniformly.

For collecting data 10 guarded/representative plants were selected in each treatment and marked for identification. Data were collected for nodes to 1st fruiting branch counted from zero node (cotyledonary node) to the node at which first flower was appeared number of days to 1st square and 1st flower plant height monopodia and sympodia per plant number of bolls per plant boll weight seed cotton yield and ginning out turn (GOT).

Earliness index was calculated as mean yield of first picking divided by total yield and multiplied by 100 of each family in each replication for the purpose of data analysis.

Fiber characteristics such as staple length fiber fineness and fiber strength of each guarded plant were measured by using spin lab HVI-900.

CLCuV disease incidence (%) and reaction of the cultivars was determined with the help of disease scale (Table 1) as described by Akhtar et al. 2010 and Farooq et al. 2011 using the following formula used by Akhtar et al. 2003 in cotton.

CLCuV disease incidence (%) = Sum of all disease ratings/total number of plants A-100/6

According to this formula Individual symptomatic plant ratings for each genotype are summed up and divided by the total number of plants to calculate the corresponding disease incidence percentage.

Statistical Analysis: The data were subjected to analysis of variance (ANOVA) using the MSTAT-C package (Russell D. Freed Michigan State University USA 1984). The means were separated using Fisher's protected Least Significance Difference test (LSD) at P = 0.05. Heritability in broad sense was estimated according to the technique of Burton and De Vane (1953). Genetic advance was calculated at 20 % selection intensity using formula given by Poehlman and Sleper (1995). All correlations (phenotypic and genotypic) were computed following the statistical technique prescribed by Kowon and Torrie (1964). Genotypic correlations were tested following the method of Lotherop et al. 1985. Statistical significance of phenotypic correlations was determined by T-test as described by Steel and Torrie (1984). Path coefficient analysis was done following to the method suggested by Dewey and Lu (1959).

RESULTS AND DISCUSSION

The means performance of 53 genotypes is given in Table-2. The data of all the traits studied showed significant differences (Table 3). PCV % was higher in magnitude than GCV% for all the traits which are in accordance with the results of Mendez-Natera et al. (2012). Ali et al. 2009 reported higher values of GCV and PCV% for fiber traits and seed cotton yield. Heritability (broad sense) revealed higher estimates for the traits like fiber strength (99%) boll weight (98%) GOT% (97%) fiber fineness (95%) staple length (91%) yield kg/ha (89%) CLCuV % (86%) plant height (77%) bolls per plant (77%) days taken to 1st flower (74%) days taken to 1st square (71%) while the traits like sympodia per plant (42%) nodes to 1st fruiting branch (35%) and monopodia per plant (34%) showed moderate heritability values. Basbeg and Gencer (2004) reported higher estimates of heritability for fiber fineness and strength but low for bolls per plant and seed cotton yield and recommended early generation selection for traits having higher heritability. Mendez-Natera et al. 2012 reported higher values of broad sense heritability for fiber fineness but moderate values for plant height fiber length and fiber strength and low values for bolls per plant boll weight and seed cotton yield. Naveed et al. 2004 reported low values of heritability for lint percentage and boll weight. Mass or early generation selection could be practiced in traits showing higher and moderate estimates of broad sense heritability in current studies. Higher values of genetic advance were observed for bolls per plant (5.16) plant height (14.2) fiber strength (5.67) earliness index (7.00) and for yield (778.7). Higher values of genetic advance for plant height (26.3) and fiber strength (3.9) were observed in the findings of Mendez- Natera et al. (2012). High heritability and genetic advance are more useful in predicting gain under selection than heritability alone. Higher magnitude of both these components is indicative of additive genetic effects thus higher genetic gain may be anticipated. The differences in the findings of various workers may be due to the variation in experimental material and environmental factors.

Genotypic and phenotypic correlations of 15 traits are presented in Table-4. Seed cotton yield had positive genotypic correlation with bolls per plant plant height boll weight staple length and strength earliness index and GOT. These results are in agreement with the findings of Ashokkumar and Ravikesavan (2010).Significant genotypic correlations followed by phenotypic correlations were observed in the present studies which are in conformity with the findings of Desalegn et al. 2009 who reported the chief role of genetic effects. Qayyum et al. 2010 also found the important role of genotypic correlation coefficients. For nodes to 1st fruiting branch positive and significant association was shown by the traits like days to 1st flower days taken to 1st square both at genotypic and phenotypic level but the CLCuV% only showed significant positive association at genotypic level. The traits like seed cotton yield bolls per plant and boll weight showed negative and significant phenotypic association with nodes to 1st fruiting branch. Contrasting results were reported by Shah et al. 2010 which reported negative correlation for nodes to 1st fruiting branch with days taken to 1st square and flower. The earliness related traits like days taken to 1st square and flower showed

positive and significant correlation with each other CLCuV% and monopodia per plant both at genotypic and phenotypic level but negative significant phenotypic correlations with seed cotton yield. The earliness index showed positive and significant genotypic correlation with bolls per plant and negative significant phenotypic estimates with CLCuV% but Shah et al. 2010 reported negative estimates with different morphological and earliness related traits.While considering sympodia per plant its significant positive genotypic and phenotypic association was found with bolls per plant plant height staple length fiber fineness and GOT. While it showed negative and significant phenotypic correlation with monopodia per plant.

The traits like plant height boll weight staple length CLCuV% and seed cotton yield had positive and significant genotypic and phenotypic correlations with bolls per plant. Only significant positive genotypic correlations were shown by the traits like GOT and days taken to 1st square. Ashokkumar and Ravikesavan (2010) reported positive correlation of sympodia per plant with boll weight and bolls per plant which are in agreement with the present studies. The earliness index% showed negatively significant phenotypic correlations with bolls per plant. Plant height had positive significant genotypic and phenotypic correlation with boll weight GOT and seed cotton yield. Correlation of plant height with bolls per plant has been reported by Ashokkumar and Ravikesavan (2010). However staple length earliness index days taken to 1st square and flowers along with CLCuV% showed positive significant genotypic association with plant height. Boll weight has positive and significant genotypic association with seed

cotton yield and negative significant phenotypic association with earliness index and days taken to 1st square. Similarassociation was reported by Ashokkumar and Ravikesavan (2010). While considering staple length it showed positive significant genotypic and phenotypic estimates with GOT and seed cotton yield. Swati Bharad et al. (1999) reported negative correlation with fiber fineness. In terms of phenotypic correlations only significant positive estimates were shown by days taken to 1st flower however days taken to 1st square and fiber fineness showed negative significant phenotypic correlations. Fiber fineness showed positive significant genotypic and phenotypic correlations with days taken to

1st flower and CLCuV% whereas it had only positive significant phenotypic association with days taken to 1st square. Negative significant phenotypic association was found for earliness index and seed cotton yield with fiber fineness. Earliness index GOT and seed cotton yield had positive significant genotypic and phenotypic correlations with fiber strength. Negative significant phenotypic correlations were found for days taken to 1st square and flower along with CLCuV% with fiber strength.

GOT had negative significant phenotypic association with days taken to 1st flower and CLCuV%. Ashokkumar and Ravikesavan (2010) found positive correlation of GOT with plant height bolls per plant and boll weight which are in disagreement with the present findings. CLCuV% had negative significant phenotypic estimates with seed cotton yield.

Path coefficient analysis results revealed that the traits like sympodia per plant (0.11) plant height (0.15) boll weight (0.15) earliness index (0.63) GOT (0.16) and days taken to 1st square (0.17) showed positive direct effect on seed cotton yield table-5. While all other traits showed negative estimates. Mendez-Natera et al. 2012 observed maximum direct effect of sympodial branches with seed cotton yield. In the path coefficient studies of Ashokkumar and Ravikesavan (2010) maximum direct effects were imposed by boll weight and sympodia per plant. Nodes to 1st fruiting branch showed negative direct effect but it exerted positive influence on seed cotton yield indirectly through bolls per plant staple length fiber strength earliness index and days taken to 1st square however it had negative indirect effects with all other traits. Days taken to 1st square exerted positive influence however days taken to 1st flower showed negative direct impact on yield. For both the traits plant height staple length and strength exerted positive indirect effect.

All the remaining traits showed negative indirect effect on seed cotton yield via days taken to 1st square and flower. Indirect effects of days to flowering influenced seed cotton yield through fiber finenesss and

50% flowering (Ashokkumar and Ravikesavan 2010). Indirect effects of Monopodia per plant influenced the seed cotton yield positively through bolls per plant staple length fiber fineness fiber strength earliness index GOT days taken to 1st square and CLCuV% but other traits showed negative estimates. Iqbal et al. 2003 reported negative direct effects of monopodia per plant on yield. Sympodia per plant showed positive direct effect on seed cotton yield. It showed positive indirect effect on yield via nodes to 1st fruiting branch Monopodia per plant plant height boll weight fiber strength and GOT. Ashokkumar and Ravikesavan (2010) found positive indirect effects of sympodia per plant via plant height bolls per plant boll weight and ginning out turn%. Bolls per plant did not showed positive direct effect on seed cotton yield however it exerted positive indirect effects via nodes to 1st fruiting branch Monopodia per plant sympodia per plant plant height boll weight fiber strength GOT and days taken to 1st square but unable to exert any positive indirect effect through other traits. Ashokkumar and Ravikesavan (2010) reported the positive role of bolls per plant via sympodia per plant boll weight and ginning out turn. Plant height had positive direct effect on yield and the traits like nodes to 1st fruiting branch monopodia and sympodia per plant boll weight fiber fineness fiber strength GOT earliness index and days taken to 1st square exerted positive indirect effect on yield.

Boll weight had positive direct effect on seed cotton yield and it has positive indirect effect via nodes to 1st fruiting branch monopodia per plant sympodia per plant plant height fiber fineness GOT days taken to 1st flower and CLCuV%. Rauf et al. 2004 observed positive

direct effect of boll weight on yield and its indirect positive effect through monopodial and sympodial branches which are also found in the current studies. The negative indirect effects were shown by the traits like bolls per plant staple length and strength earliness index% and days taken to 1st square. Negative indirect effects of boll weight on bolls per plant were reported by Rauf et al. 2004.The staple length showed negative direct effect on yield however it had positive indirect effect via nodes to 1st fruiting branch monopodia and sympodia per plant plant height boll weight fiber fineness and strength earliness index GOT days taken to 1st flower and CLCuV%. The negative indirect effect was observed through bolls per plant and days taken to 1st square. Negative direct effects of fiber length on yield were also reported by Iqbal et al. 2003. Fiber fineness also had negative direct effect on yield but had positive indirect effect through monopodia per plant sympodia per plant staple length strength and days taken to 1st square. The remaining traits exerted negative indirect effects on yield. Same like fiber fineness and length fiber strength had negative direct effect on seed cotton yield but traits like nodes to 1st fruiting branch monopodia per plant bolls per plant boll weight staple length fineness earliness index days taken to 1st flower and CLCuV% exerted positive indirect effects. However all other remaining traits showed negative indirect effect on seed cotton yield. Maximum positive direct effect on seed cotton yield was shown by the trait earliness index. It showed positive indirect influence via bolls per

plant plant height fiber fineness GOT days taken to 1st square and flower and CLCuV% on seed cotton yield while showed negative indirect effects via all the remaining traits. GOT showed positive direct effect on seed cotton yield but negative indirect effects were observed through monopodia per plant bolls per plant staple length strength and days taken to 1st square. All the remaining traits exerted positive indirect influence on seed cotton yield. CLCuV% showed negative direct effect on yield. The traits like Monopodia and sympodia per plant plant height staple length strength and days taken to 1st square showed positive but indirect influence on yield and nodes to 1st fruiting branch bolls per plant boll weight fiber fineness earliness index GOT and days taken to 1st flower showed negative impact.

Table 1. Rating scale for cotton leaf curl virus (CLCuV) symptoms

###Symptoms###Disease###Disease###Disease

###rating###index (%)###reaction

Absence of symptoms.###0###0###Immune

Thickening of a few small veins or the presence of leaf enations on 10 or###1###0.1- 1###Highly

fewer leaves of a plant.###resistant

Thickening of a small group of veins.###2###1.1- 5###Resistant

Thickening of all veins but no leaf curling.###3###5.1-10###Moderately

###resistant

Severe vein thickening and leaf curling on the top third of the plant.###4###10.1 15###Moderately

###susceptible

Severe vein thickening and leaf curling on the half of the plant.###5###15.1 20###Susceptible

Severe vein thickening leaf curling and stunting of the plant with###6###greater than 20###Highly

reduced fruit production.###susceptible

Table 2.Mean performance of 53 genotypes/ strains in terms of earliness fiber quality CLCuV% and yield contributing traits in cotton.

###CLCuV

###PH###BWT###SL###FF###FS###EI###GOT###Yield

Genotypes###NTFFB###MPP###SPP###BPP###DFS###DFF###(%)

###(cm)###(g)###(mm)###(g/inch)###(tppsi)###(%)###(%)###(kg/ha)

FH-142###6###2###18###29###140###4.6###28.0###4.2###99.7###74###38.2###29###49###0.1###2696

FH-162###7###1###23###34###177###4.4###28.3###5.1###99.9###74###41.5###29###49###3.3###3041

FH-163###6###1###21###33###160###4.0###29.0###5.1###93.8###65###38.9###29###49###2.8###2806

FH-167###6###1###23###34###174###4.8###30.5###5.1###92.7###66###38.2###28###49###3.5###2892

FH-172###6###2###20###34###153###4.3###31.0###4.1###90.3###69###38.8###29###49###2.3###2681

FH-184###6###1###24###42###192###4.7###30.0###5.2###92.4###69###39.5###30###50###2.7###3424

FH-113###6###2###21###30###153###3.8###27.5###5.4###90.4###67###36.8###31###50###5.2###2930

IR-3701###7###2###17###19###146###3.5###27.5###5.0###87.7###60###38.1###30###50###1.6###1403

FH-201###8###3###20###25###171###3.8###28.5###4.5###91.3###77###38.2###29###50###0.2###2545

FH-202###8###2###21###25###171###3.5###30.0###4.2###98.7###80###38.6###30###50###1.0###2925

FH-203###7###3###18###27###169###4.4###28.0###5.0###95.5###81###38.6###30###50###1.7###3197

FH-204###7###3###20###20###141###4.4###27.5###5.5###90.0###62###38.4###30###50###2.1###1291

FH-205###7###2###21###24###167###3.9###27.3###5.0###98.6###81###38.3###30###49###1.4###3303

FH-206###8###2###18###26###147###3.9###28.5###4.9###93.4###84###39.2###30###50###0.2###3252

FH-208###7###1###21###28###165###3.9###27.2###5.5###95.2###75###38.0###29###49###1.0###2930

FH-209###8###2###18###27###169###4.0###30.0###5.0###94.6###73###42.0###30###49###1.9###2355

FH-210###8###2###20###24###162###3.1###28.0###5.2###96.5###72###39.9###30###49###0.9###2997

FH-211###8###2###20###29###159###4.3###28.0###5.1###94.4###77###38.5###30###50###1.5###2513

FH-212###7###2###21###31###168###4.5###28.3###5.1###87.4###81###38.8###31###50###2.7###2777

FH-213###10###2###20###30###166###4.0###27.6###5.3###92.3###74###38.2###31###50###2.1###2197

FH-215###8###2###23###30###160###4.0###28.2###5.3###100.0###76###41.0###31###51###1.4###1573

FH-2015###7###2###21###34###167###4.0###27.8###5.3###90.2###80###38.3###32###51###7.3###2396

FH-4243###6###2###21###16###157###3.7###27.8###5.2###89.5###61###36.5###31###50###4.0###1174

FH-146###8###2###21###23###178###3.3###26.5###5.1###90.0###88###39.0###30###49###4.8###2135

FH-147###7###2###19###30###158###4.1###27.2###5.2###100.1###81###38.2###31###51###5.9###2253

FH-148###8###2###19###20###124###3.0###31.0###5.3###89.1###79###38.2###31###50###4.8###1976

FH-149###7###2###22###23###165###3.4###27.2###5.1###96.0###82###40.0###31###51###2.0###1638

FH-150###7###2###21###27###165###3.8###28.0###5.0###91.0###86###38.1###30###50###1.5###2978

FH-151###7###3###21###32###152###3.8###28.5###5.1###92.5###81###39.6###29###48###2.0###3217

FH-152###8###1###21###28###172###4.0###27.0###5.0###101.0###77###38.3###31###51###3.5###2550

FH-154###7###2###21###32###162###3.8###29.0###4.6###89.0###79###38.3###30###49###5.9###2585

FH-155###8###2###22###27###175###4.1###30.0###4.8###93.0###76###41.6###30###49###1.6###2843

FH-157###8###2###20###33###172###3.9###28.3###5.0###90.2###68###38.8###32###51###2.6###2422

FH-160###7###2###22###39###188###4.8###29.0###4.8###91.9###69###38.6###31###50###4.7###2557

FH-164###8###1###20###31###181###4.3###30.0###4.9###86.2###79###38.3###31###51###5.7###2164

FH-194###6###2###23###37###189###3.6###28.2###5.0###85.6###79###38.5###31###50###1.3###2427

Table 3. Mean squares genotypic and phenotypic coefficients of variation heritability and genetic advance for various traits of 53 genotypes/strains of cotton

Characters###Mean squares###GCV (%)###PCV (%)###Heritability (%)###GA (%)

NTFFB###2.52###7.49###12.60###35###0.45

MPP###1.17###17.10###29.16###34###0.30

SPP###10.52###5.90###9.04###43###1.12

BPP###68.07###14.42###16.40###77###5.16

PH###511.72###6.91###7.85###77###14.2

BW###0.59###10.96###11.06###98###0.61

SL###4.17###3.97###4.15###91###1.51

FF###0.32###6.42###6.56###96###0.44

FS###50.03###4.39###4.41###99###5.67

EI (%)###159.30###8.21###9.85###70###7.00

GOT (%)###4.38###3.06###3.11###97###1.65

DFS###2.24###2.40###2.85###71###0.86

DFF###2.88###1.69###1.96###74###1.00

CLCuV%###17.87###71.38###76.77###86###2.95

Yield (kg/ha)###1162327.98###23.52###24.88###89###778.7

Table-4. Genotypic and phenotypic Correlation coefficient of various plant traits in cotton

###NTFFB###MPP###SPP###BPP###PH###BW###SL###FF###FS###EI###GOT###DFS###DFF###CLCuV###Yield

###(cm)###(g)###(mm)###(g/inch)###(tppsi)###(%)###(%)###%###(kg/ha)

###rg###1.00###0.40###-0.08###-0.44###-0.01###-0.55###-0.21###0.16###-0.10###0.12###-0.05###0.35###0.65###0.21###-0.44

NTFFB

###rp###0.03###0.01###-0.19###0.04###-0.34###-0.10###0.11###-0.06###0.11###-0.02###0.21###0.29###0.12###-0.21

###rg###1.00###-0.45###-0.69###-0.03###-0.13###-0.22###-0.13###-0.12###0.28###0.20###0.65###0.61###-0.13###-0.16

MPP

###rp###-0.21###-0.35###-0.01###-0.09###-0.14###-0.07###-0.07###0.13###0.10###0.28###0.24###-0.02###-0.08

###rg###1.00###0.67###0.75###0.03###0.33###0.37###-0.04###-0.29###0.30###-0.12###0.01###0.24###0.01

SPP

###rp###0.42###0.44###0.02###0.18###0.20###-0.03###-0.09###0.17###0.01###0.06###0.13###0.02

###rg###1.00###0.54###0.51###0.28###0.01###-0.14###-0.27###0.09###0.12###0.08###0.33###0.23

BPP

###rp###0.46###0.44###0.23###0.01###-0.12###-0.16###0.06###0.11###0.03###0.25###0.21

###rg###1.00###0.36###0.10###-0.13###-0.05###0.06###0.22###0.10###0.23###0.15###0.23

PH (cm)

###rp###0.31###0.08###-0.11###-0.06###0.07###0.18###0.12###0.14###0.13###0.21

###rg###1.00###0.12###-0.15###0.11###-0.27###0.13###-0.25###-0.08###-0.12###0.12

BW (g)

###rp###0.12###-0.14###0.11###-0.23###0.13###-0.21###-0.06###-0.12###0.11

###rg###1.00###-0.47###-0.14###0.03###0.25###-0.25###-0.32###-0.10###0.34

SL (mm)

###rp###-0.44###-0.14###0.02###0.25###-0.21###0.26###-0.10###0.30

FF###rg###1.00###-0.23###-0.30###-0.07###0.33###0.37###0.27###-0.40

(g/inch)###rp###-0.21###-0.25###-0.06###0.26###0.30###0.26###-0.37

###rg###1.00###0.34###0.35###-0.38###-0.34###-0.40###0.37

FS (tppsi)

###rp###0.28###0.35###-0.32###-0.29###-0.37###0.35

###rg###1.00###0.33###0.05###-0.11###-0.25###0.60

EI (%)

###rp###0.28###0.03###-0.09###-0.23###0.52

###rg###1.00###-0.14###-0.20###-0.44###0.34

GOT (%)

###rp###-0.12###-0.18###-0.40###0.32

###rg###1.00###0.98###0.64###-0.51

DFB

###rp###0.75###0.47###-0.39

###rg###1.00###0.42###-0.63

DFS

###rp###0.33###-0.50

###rg###1.00###-0.31

CLCuV(%)

###rp###-0.30

###rg###1.00

Y (kg/ha)

Table 5. Direct (diagonal) and Indirect (off-diagonal) effects of various plant traits in cotton

###NTFFB###MPP###SPP###BPP###PH###BW###SL###FF###FS###EI###GOT###DFS###DFF###CLCuV%###rg

###(cm)###(g)###(mm) (g/inch) (tppsi)###(%)###(%)

NTFFB###-0.3023 -0.2050 -0.0098###0.1473###-0.0028###-0.0841###0.0020 -0.0409 0.0114###0.0756###-0.0082###0.0605###-0.0755###-0.0108###-0.4426

MPP###-0.1224 -0.5064 -0.0522###0.2304###-0.0058###-0.0204###0.0021 0.0338 0.0131###0.1809###0.0330###0.1127###-0.0713###0.0069###-0.1656

SPP###0.0259 0.2326 0.1137###-0.2225###0.1160###0.0051###-0.0032 -0.0900 0.0042###-0.1883###0.0499###-0.0220###-0.0012###-0.0128###0.0075

BPP###0.1342 0.3517 0.0763###-0.3317###0.0838###0.0770###-0.0026 -0.0016 0.0154###-0.1765###0.0139###0.0216###-0.0093###-0.0172###0.2349

PH(cm)###0.0054 0.0190 0.0857###-0.1806###0.1540###0.0555###-0.0010 0.0315 0.0062###0.0423###0.0366###0.0182###-0.0271###-0.0081###0.2375

BW(g)###0.1685 0.0684 0.0039###-0.1694###0.0566###0.1508###-0.0012 0.0364 -0.0117###-0.1721###0.0221###-0.0438###0.0095###0.0066###0.1246

SL(mm)###0.0637 0.1137 0.0386###-0.0931###0.0161###0.0184###-0.0094 0.1140 0.0149###0.0241###0.0419###-0.0445###0.0376###0.0054###0.3413

FF(g/inch) -0.0512 0.0708 0.0423###-0.0022###-0.0200###-0.0227###0.0045 -0.2418 0.0240###-0.1922###-0.0122###0.0572###-0.0431###-0.0146###-0.4013

FS(tppsi)###0.0332 0.0638 -0.0046###0.0490###-0.0092###0.0170###0.0014 0.0559 -0.1039###0.2182###0.0586###-0.0671###0.0401###0.0210###0.3736

EI (%)###-0.0361 -0.1449 -0.0339###0.0926###0.0103###-0.0411###-0.0004 0.0735 -0.0358###0.6323###0.0541###0.0092###0.0133###0.0131###0.6062

GOT (%)###0.0151 -0.1021 0.0347###-0.0281###0.0344###0.0203###-0.0024 0.0180 -0.0372###0.2090###0.1637###-0.0255###0.0237###0.0233###0.3468

DFB###-0.1062 -0.3313 -0.0145###-0.0416###0.0163###-0.0384###0.0024 -0.0802 0.0404###0.0338###-0.0243###0.1723###-0.1136###-0.0335###-0.5182

DFS###-0.1986 -0.3139 0.0012###-0.0267###0.0363###-0.0125###0.0031 -0.0906 0.0362###-0.0733###-0.0338###0.1702###-0.1150###-0.0223###-0.6396

CLCuV%###-0.0629 0.0670 0.0279###-0.1095###0.0239###-0.0190###0.0010 -0.0676 0.0418###-0.1586###-0.0731###0.1107###-0.0493###-0.0521###-0.3198

Conclusion: Heritability estimates were higher for most of the traits except for nodes to 1st fruiting branch monopodia and sympodia per plant which showed moderate values. Maximum values of genetic advance were observed for seed cotton yield plant height and earliness index. Characters showing high heritability and genetic advance may be further evaluated through early generation selection as increased values of both are indicative of additive genetic effects. Bolls per plant plant height boll weight staple length and strength earliness index and GOT had positive genotypic correlation with seed cotton yield and have reasonable heritability thus may be used as selection criteria to enhance seed cotton yield

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ZCZC SCREENING FOR RESISTANCE TO CUCUMBER MOSAIC CUCUMOVIRUS IN CHILLI PEPPER

By: M. Ashfaq S. Iqbal T. Mukhtar and H. Shah

_: ABSTRACT

Cucumber mosaic cucumovirus (CMV) is destructive pathogen with widest host range infecting more than 100 botanical families comprising more than 500 genera and 1300 plant species. Chilli pepper is a significant cash crop of Pakistan among vegetable grown. The identification of genetic resistance to CMV in Pakistan (CMV chilli isolate) in chilli pepper is of economic importance. Thus 40 Chilli pepper genotypes both local and imported were evaluated by mechanical/ manual virus inoculation and resistance to CMV chilli isolate was examined by visual observations and enzyme-linked immunosorbent assay (DAS-ELISA). On the basis of 0-5 disease rating scale and ELISA nine genotypes viz. C-2 CV- 2 CV-5 BSS-269 PGRI M-2001 CM-2001 M-97 and CP-328 were remained free of infection and catalogued as highly resistant. Rest of the genotypes exhibited characteristic symptoms like mosaic mottling leaf curling and reduced leaf size depending upon tested genotypes. Among these genotypes five were categorized as resistant seven as moderately resistant eight as moderately susceptible and 11 as susceptible. These resistant and moderate resistant genotypes could be used by farmers in cultivation under integrated production systems and by breeders in developing new chilli pepper hybrid resistant genotypes to CMV.

Key words: Chilli pepper Cucumber mosaic virus resistant ELISA.

INTRODUCTION

Chilli pepper (Capsicum annum L.) is one of the most important members of solanaceous vegetables grown in Pakistan and ranked at third position after potato and tomato (Iqbal et al. 2012). Chilli contains more vitamins C than any other vegetable crop (Dexiang 1994). Among the various factors limiting to chilli production in Pakistan viruses appear to be significant production constraints. Among these viruses Cucumber mosaic virus (CMV) causes severe/ economic yield reduction in chillies. Doolittle (1916) and Jagger (1916) first described Cucumber mosaic virus (CMV) and the virus was assigned to the Cucumovirus group as the type member. CMV is tri-partite single-stranded +ive sense RNA virus. Intrinsically RNA viruses are heterogeneous and to a certain extent their heterogeneous nature is because of error-prone nature of RNA replication (Ding et al. 1995; Domingo and Holland 1994). CMV has a very broad host range of wild and cultivated plants with more than 1300 known hosts including

some monocotyledons and a great number of dicotyledons (Chen et al. 2006). Tomlinson (1978) described CMV as the most economically important virus in cowpea celery cucurbits pepper lettuce and tomato. Other researchers (Palukaitis et al. 1992; Gafny et al. 1996 Davis et al. 1996 Latham et al. 1999) reported that Banana Pasture legumes Kava and ornamentals are also affected by CMV. CMV is easily transmitted by mechanical inoculation of plant sap and naturally transmitted (non- persistently) by 80 aphid species (Palukaitis and Garcia- Arenal 2003). Use of disease resistant crop varieties is regarded as an economical and durable method for controlling plant diseases especially those caused by viruses. Recently the role of mineral metabolism and total soluble phenols in imparting resistance/susceptibility against viral diseases of plants has also been manifested (Ashfaq et al. 2014). A good deal of research work has been directed to identify resistant sources under diverse environmental conditions and continuing screening of available genotypes and new germplasm which constitutes the basis of this work has been suggested by several research workers ( Bashir et al. 2005; Ashfaq et al. 2007; Ashfaq et al. 2008; Ashfaq et al. 2014). Therefore to evaluate and catalogue sources of CMV resistant genotypes forty local and exotic chilli pepper genotypes were screened by mechanical inoculation.

The level of resistance to CMV accumulation in chilli pepper leaf tissues was evaluated using a combination of visual symptom observations and enzyme-linked immunosorbent assay (ELISA).

MATERIAL AND METHODS

Virus source and maintenance: A Pakistani isolate of chilli pepper infecting CMV (CMV chilli isolate) was used as virus source for mechanical inoculation (Iqbal et al. 2011). The virus was propagated and maintained in Nicotiana benthamiana plants.

Plant materials: Forty different Capsicum genotypes were obtained from Asian Vegetable Research and Development Center (AVRDC) Taiwan Vegetable Research Program Horticultural Research Institute (HRI) NARC and Mexico (Table 1). Twenty seeds of each genotype were sown in small clay pots that contained a sterilized soil mixture composed of peat clay and sand mixed in equal ratio of 1:1:1 under green house conditions. At 2-3 leaf stage the Capsicum seedlings were transplanted to plastic pots (2 seedlings per pot) and 1% urea solution was applied to each pot to enhance the vegetative growth.

Mechanical inoculation: Symptomatic leaves of Nicotiana benthamiana inoculated with CMV chilli isolate were harvested and one gram of these leaf tissues used as inoculums and homogenized (1/3 w/v) in 0.05 M phosphate buffer pH 7.2 containing 1% Na2SO3. The Capsicum plants at the two leaf stage were rub-inoculated with sap extract as described by Ashfaq et al. (2010). After inoculation the plants were rinsed with distilled water to remove superfluous inoculum and kept in an insect free glasshouse (25oC temperature and 70% humidity). The un-inoculated plants (healthy plants) of each test genotype were maintained as control. The symptoms on the host plants were recorded according to disease rating scale (0-5) as used by Shah et al. (2011) and genotypes were categorized as HR (Highly Resistant with 0-10% infection) R (Resistant with 11-20% infection) MR (Moderately resistant with 21-30% infection) MS (Moderately susceptible with 31-50% infection) S (Susceptible with greater than 50 infection) on the basis of host reaction.

Serological assay: DAS-ELISA (Double Antibody Sandwich- ELISA) tests were employed (Clark and Adam 1977; Verma et al. 2005) for investigation of virus in leaves of Capsicum genotype after four weeks of inoculation. Polystyrene plates were coated with anti- CMV antibodies (Bioreba AG Switzerland) diluted 1:200 in coating buffer and incubated overnight at 4 oC. Sap was extracted by grinding leaves in the extraction buffer in pestle and mortar and then filtered through the double layered muslin cloth. Exactly 200l of the extracted sap of each sample was then added to the coated polystyrene plate and incubated overnight at 4oC. Alkaline phosphatase-conjugated anti-CMV antibodies (Bioreba AG) were added and incubated overnight at 4 oC followed by incubation with p-nitrophenyl phosphate (MP Biomedicals Inc. Ohio USA) at room temperature for 1 h. The absorbance values (405 nm) were measured with an Automatic ELISA Reader (HER-480 HT Company (Illford) Ltd. UK). Samples were considered positive for CMV infection when the ELISA absorbance value was equal to two times or higher than the average of absorbance value of the healthy tissue as well as negative control. Commercial positive and negative controls (Bioreba) were included in CMV ELISA kit.

RESULTS

Results on reaction of Chilli germplasm consisting of 40 genotypes both local and imported against Cucumber mosaic virus (CMV) under controlled conditions are given in Table 1. Thirty-one of forty genotypes showed systemic symptoms of CMV including mosaic mottling leaf curling necrosis upward curling yellowing and smalling of leaves (Table 1). Individual plants of C-1 C-11 CV-10 CV-21 MI-2 PTY-8 PTY- 11 PBC-149 PBC-518 NARC-4 ( SAVERNET chilli- pepper genotypes) and GM-2001 (Mexico-chilli pepper genotype) showed mosaic mottle leaf curling necrosis yellowing and smalling of leaves and symptoms developed at 10 days post inoculation (dpi) while other genotypes exhibited symptoms between 18 and 24 dpi. All of these eleven genotypes exhibited 57.14-100 % CMV infection on the basis of 0-5 disease rating scale with relatively high titre (greater than 1.0) detection in the upper symptomatic leaves so considered all of these susceptible to CMV chilli isolate. Similarly on the basis of disease rating scale (0-5) and ELISA tests eight genotypes viz. C-4 C-5 PTY-10 PBC-386 and PBC-495 (SAVERNET chilli pepper genotypes) sanam chilli 0027 and chilli 007 (Pakistan local chilli pepper genotypes) were grouped as moderate susceptible.

On the other hand the nine genotypes viz. C-2 CV-2 CV-5 BSS-269 PGRI M-2001 CM-2001 M-97 and CP-328 did not manifest any symptom as well as CMV detection in relatively low titer (less than 0.25) in the upper leaves and therefore catalogued as highly resistant against

CMV. Similarly five genotypes viz. C-10 CV-1 CV-12 PBC-142 and PBC-385 and rest of the seven genotypes viz. C-6 C-7 C-8 CV-7 CV-9( SAVERNET chilli- pepper genotypes) chilli 0013 and swat local (Pakistan local chilli pepper genotypes) were regarded as resistant and moderately resistant respectively based on both disease rating scale and ELISA tests (Table 1).

Table 1. Reaction of Capsicum genotypes against CMV under glass house conditions.

Pepper###Total###Infected###ELISA###CMV%###Type of###Remarks

genotypes###plants###plants.###reading for###Infection###symptoms

###tested.###CMV###observed

###SAVERNET chilli-pepper genotypes

###C-1###18###12###1.253###66.66###M m LC###S

###C-2###12###0###0.125###0###NS###HR

###C-4###13###5###0.688###38.46###M LC###MS

###C-5###14###5###0.602###35.71###M LC###MS

###C-6###16###4###0.593###25###M m###MR

###C-7###12###3###0.593###25###M UC###MR

###C-8###8###2###0.593###25###M LC###MR

###C-10###18###3###0.322###16.66###M###R

###C-11###15###15###1.236###100###M YN SL###S

###CV-1###14###2###0.225###14.28###M###R

###CV-2###14###0###0.232###0###NS###HR

###CV-5###16###0###0.232###0###NS###HR

###CV-7###15###4###0.600###26.66###M m###MR

###CV-9###15###3###0.502###20###M###MR

###CV-10###18###11###1.084###61.11###M SL###S

###CV-12###17###2###0.2252###14.28###M###R

###CV-21###16###9###1.085###56.25###M LC###S

###MI-2###20###12###1.053###60###MmLL###S

###PTY-8###16###10###1.251###62###M LC###S

###PTY-10###16###6###0.556###37.50###MUL###MS

###PTY-11###14###8###1.245###57.14###M LC###S

###PBC-386###18###6###0.489###33.33###Mm###MS

###PBC-495###15###5###0.565###33.33###Mm###MS

###PBC-142###14###4###0.265###28.57###M###R

###PBC-518###16###10###1.223###62.5###Mm SL###S

###PBC-149###13###13###2.333###100###m LC Y###S

###BSS-269###12###0###0.232###0###NS###HR

###NARC-4###15###9###1.069###60###M m SL###S

###PGRI###12###0###0.232###0###NS###HR

###Mexico- Chilli pepper genotypes

###M-2001###15###0###0.26###0###NS###HR

###GM-2001###14###14###1.23###100###M Y SL###S

###CM-2001###10###0###0.167###0###NS###HR

###M-97###13###0###0.125###0###NS###HR

###CP-328###11###0###0.049###0###NS###HR

###Pakistan Local Chilli pepper genotypes

###Sanam###15###7###0.753###46.66 %###M LC###MS

###Chili 0027###12###4###0.602###33.33 %###M UC###MS

###Chili 0013###16###4###0.439###25 %###M###MR

###Chili 007###13###5###0.688###38.46 %###M UL###MS

###Swat local###18###5###0.45###27.78 %###M###MR

###PBC 385###19###4###0.39###21.05 %###M###R

DISCUSSION

In view of ubiquitous nature of CMV disease 40 chilli genotypes were evaluated against CMV under green house conditions. The genotypes were classified into five reaction groups based upon % infected plants and ELISA test. These were: highly resistant resistant moderately resistant moderately susceptible and susceptible. The mean percentage genotypes falling in the categories were: 22.50 12.50 17.50 20.0 and 27.50 respectively. It is apparent from the above results that all local genotypes were susceptible to CMV infection except PBC-385 that showed high resistant response to CMV and all Mexican genotypes viz. M-2001 CM-

2001 M-97 and CP-328 were remained highly resistant to CMV infection except GM-2001. However Asian Vegetable Research and Development Center lines i.e. C-2 CV-2 CV-5 BSS-269 and PGRI were resistant to CMV where as other genotypes showed susceptibility to CMV when inoculated under glasshouse conditions. These results are in agreement with Rashid et al. (2007) who did not observe any infection by ELISA in C-1 C-2 C-5 C-7C-9 C-11except the pepper lines C-4 C-8C-9 and local check which did show positive reaction to

CMV while in the present study the lines C-6 C-7 C-8 CV-7 CV-9 exhibited moderately resistant reaction whereas the genotypes C-4 C-5 PTY-10 PBC-386 and PBC-495 showed moderately susceptible reaction. Only two genotypes viz. C-7 and C-8 showed different response of reaction and this might be due to disease escape because the Rashid et al. (2007) made their study under natural conditions.

In Pakistan no systematic work has been conducted to determine the yield losses due to viral diseases on chilli crop. CMV is one of the major pepper viruses recorded in world elsewhere including Pakistan (Iqbal et al. 2012; Green and Kim 1991). But under the field condition it is difficult to predict the existence of virus species because of the complex nature of the viruses infection i.e. more than two viruses occur in combination e.g. TMV PVY ChiVMV and so on (Green and Kim1991; Shah et al. 2001). As Cucumber mosaic virus is one of the major virus that is known to have broad host range so it is not easy to control it. Usually the conventional measures like cross protection eradication of infected plants crop rotation use of virus free plants and use of chemicals against vectors has been practiced since a long time to control or manage the plant viral diseases (Boss 2000; Hull 2014). Anyhow use of resistant varieties is considered as an economical and durable method for controlling viral diseases and therefore management of viral diseases has always been focused on control of insect-vector and use of resistant varieties. The present findings suggest that the genotypes showing resistance to CMV local isolate should be need to be maintained for further studies for locating resistance sources under field conditions and for genetic manipulations and breeding purpose. One main problem in germplasm evaluation is that some genotypes found resistance at one location turn out

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Publication:Journal of Animal and Plant Sciences
Geographic Code:9PAKI
Date:Jun 30, 2014
Words:9342
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