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Acharya N G Ranga Agricultural University, Guntur

The Andhra Pradesh Agricultural University (APAU) was established on 12th June 1964 at Hyderabad. The University was formally inaugurated on 20th March 1965 by Late Shri. Lal Bahadur Shastri, the then Hon`ble Prime Minister of India. Another significant milestone was the inauguration of the building programme of the university by Late Smt. Indira Gandhi,the then Hon`ble Prime Minister of India on 23rd June 1966. The University was renamed as Acharya N. G. Ranga Agricultural University on 7th November 1996 in honour and memory of an outstanding parliamentarian Acharya Nayukulu Gogineni Ranga, who rendered remarkable selfless service for the cause of farmers and is regarded as an outstanding educationist, kisan leader and freedom fighter. HISTORICAL MILESTONE Acharya N. G. Ranga Agricultural University (ANGRAU) was established under the name of Andhra Pradesh Agricultural University (APAU) on the 12th of June 1964 through the APAU Act 1963. Later, it was renamed as Acharya N. G. Ranga Agricultural University on the 7th of November, 1996 in honour and memory of the noted Parliamentarian and Kisan Leader, Acharya N. G. Ranga. At the verge of completion of Golden Jubilee Year of the ANGRAU, it has given birth to a new State Agricultural University namely Prof. Jayashankar Telangana State Agricultural University with the bifurcation of the state of Andhra Pradesh as per the Andhra Pradesh Reorganization Act 2014. The ANGRAU at LAM, Guntur is serving the students and the farmers of 13 districts of new State of Andhra Pradesh with renewed interest and dedication. Genesis of ANGRAU in service of the farmers 1926: The Royal Commission emphasized the need for a strong research base for agricultural development in the country... 1949: The Radhakrishnan Commission (1949) on University Education led to the establishment of Rural Universities for the overall development of agriculture and rural life in the country... 1955: First Joint Indo-American Team studied the status and future needs of agricultural education in the country... 1960: Second Joint Indo-American Team (1960) headed by Dr. M. S. Randhawa, the then Vice-President of Indian Council of Agricultural Research recommended specifically the establishment of Farm Universities and spelt out the basic objectives of these Universities as Institutional Autonomy, inclusion of Agriculture, Veterinary / Animal Husbandry and Home Science, Integration of Teaching, Research and Extension... 1963: The Andhra Pradesh Agricultural University (APAU) Act enacted... June 12th 1964: Andhra Pradesh Agricultural University (APAU) was established at Hyderabad with Shri. O. Pulla Reddi, I.C.S. (Retired) was the first founder Vice-Chancellor of the University... June 1964: Re-affilitation of Colleges of Agriculture and Veterinary Science, Hyderabad (estt. in 1961, affiliated to Osmania University), Agricultural College, Bapatla (estt. in 1945, affiliated to Andhra University), Sri Venkateswara Agricultural College, Tirupati and Andhra Veterinary College, Tirupati (estt. in 1961, affiliated to Sri Venkateswara University)... 20th March 1965: Formal inauguration of APAU by Late Shri. Lal Bahadur Shastri, the then Hon`ble Prime Minister of India... 1964-66: The report of the Second National Education Commission headed by Dr. D.S. Kothari, Chairman of the University Grants Commission stressed the need for establishing at least one Agricultural University in each Indian State... 23, June 1966: Inauguration of the Administrative building of the university by Late Smt. Indira Gandhi, the then Hon`ble Prime Minister of India... July, 1966: Transfer of 41 Agricultural Research Stations, functioning under the Department of Agriculture... May, 1967: Transfer of Four Research Stations of the Animal Husbandry Department... 7th November 1996: Renaming of University as Acharya N. G. Ranga Agricultural University in honour and memory of an outstanding parliamentarian Acharya Nayukulu Gogineni Ranga... 15th July 2005: Establishment of Sri Venkateswara Veterinary University (SVVU) bifurcating ANGRAU by Act 18 of 2005... 26th June 2007: Establishment of Andhra Pradesh Horticultural University (APHU) bifurcating ANGRAU by the Act 30 of 2007... 2nd June 2014 As per the Andhra Pradesh Reorganization Act 2014, ANGRAU is now... serving the students and the farmers of 13 districts of new State of Andhra Pradesh with renewed interest and dedication...

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Subject: Genetics and Plant Breeding × End date: 2023 × Start date: 2022 × Type: Thesis × Thesis Type: Ph.D ×
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    ThesisItemOpen Access
    GENETIC ANALYSIS IN BLACKGRAM [Vigna mungo (L.) Hepper] FOR YIELD AND ITS COMPONENTS
    (Acharya N G Ranga Agricultural University, 2023-12-07) Y. PUSHPA RENI; M.V. RAMANA
    The current study, "Genetic analysis in blackgram [Vigna mungo (L.) Hepper] for yield and its components," was conducted from 2019 to 2021 at Regional Agricultural Research station, Lam Farm, Guntur, Andhra Pradesh. The study's main goal was to comprehend the type of gene action that underlies the inheritance of seed yield and yield contributing traits, as well as quality traits. In order to fully understand epistasis, generation mean analysis of a five-parameter model was performed. In this process, fifty nine genotypes including four checks of blackgram were evaluated for yield and yield attributing characters viz., days to 50 per cent flowering, days to maturity, plant height, number of branches per plant, number of clusters per plant, number of pods per plant, pod length, number of seeds per pod, 100 seed weight, harvest index, protein content, iron content, zinc content, MYMV incidence, leaf curl incidence and seed yield per plant during kharif, 2019 to study the diversity analysis and to identify the parents having resistance to MYMV and high yielding traits. Six parents from this material are used as parents to generate 15 crosses in half diallel fashion and these F1’s were evaluated during kharif, 2020. Out of fifteen crosses three best crosses were selected based on combining ability, heterosis and MYMV reaction studies, further to generate F2’s and F3’s. Parents, F1’s, F2’s and F3’s were evaluated during Rabi, 2020-21 to study the gene effects for yield and yield attributing characters. The analysis of variance (ANOVA) indicated significant genotype differences for each character, showing that the genotypes under study have a sizable degree of variability and intrinsic genetic diversity. PCV values are higher than GCV values, indicating the role of the environment in the expression of these traits. High heritability coupled with high genetic advance as percent mean was perceived for plant height, number of branches per plant, number of clusters per plant, number of pods per plant, seed yield per plant, harvest index, iron content and zinc content specified the predominance of additive gene action in the expression of these traits. xvii By using Mahalanobis D2 statistic, PCA and ward’s method and per se performance, the genotypes LBG 904, LBG 752, TU 94-2 and TBG 129 were used in the crossing programme along with TU 40 and PU 31, as they (PU 31 & TU 40) are a potential source of YMV and leaf curl virus resistance as per earlier reports of MULLaRP. From the results of the correlation studies, yield related traits like number of pods per plant, harvest index, number of clusters per plant, number of seeds per pod, days to 50% flowering, 100 seed weight, number of branches per plant, pod length and plant height could be utilized as selection criteria for improving seed yield in blackgram. According to the residual effects for the current study, which is 0.1720, the analysed features were responsible for almost 83% of the variability in the dependent variable, seed yield per plant. Out of the fifty nine genotypes, 51 were found to be resistant with a disease score of ‘1-2.’ Four genotypes scored ‘3-4’ on the disease reaction scale, which denotes a moderate level of resistance. Six parents viz., LBG 904, LBG 752, TU 94-2, TBG 129, PU 31 and TU 40 and their 15 crosses were generated by crossing in a half diallel fashion for fourteen traits including yield, yield attributing traits and quality traits to obtain the information on their per se performance, combining ability and heterosis. Analysis of variance revealed significant differences among the genotypes for most of the traits indicating the existence of sufficient variability in the material. Based on per se and gca effects, the parents LBG 752, LBG 904, and TBG 129 were shown to be the best combiners for yield and yield characteristics. For zinc content, PU 31 and TBG 129 are good combiners. According to the results of the sca effects, the crosses LBG 904 x TBG 129, LBG 904 x PU 31, LBG 752 x TU 40 and PU 31 x TBG 129 were found to be superior cross combinations for the majority of yield attributes and a few quality traits, while the crosses PU 31 x TBG 129, PU31 x TU 40 and TU 94-2 x TU 40 showed good mean and sca for quality traits with early maturity. Heterosis studies revealed that the crosses LBG 752 x TBG 129, LBG 904 x TBG 129, and PU 31 x TBG 129 manifested significant mid parents, a better parent and standard heterosis in a desirable direction for the majority of the yield, yield attributes and few quality traits and with early maturity. Partitioning of variance indicated that mean values [m] for gene effects were highly significant for all the characters in all three crosses. The significance of epistatic effects, in addition to the major components, additive and dominance gene effects, was revealed by the generation mean analysis for yield and yield components in the three best cross combinations, LBG 752 x TBG 129, LBG 904 x TBG 129, and PU 31 x TBG 129. Both duplicate and complimentary type of epistasis were observed in three crosses, but the majority of features are influenced by complimentary type of epistasis in addition to additive gene effects, indicating that these genotypes have the ability to create positive transgressive segregants. In presence of such additive x additive type of inter-allelic interaction with complementary type of epistasis, can be exploited using breeding methods which fix the additive effects and facilitate in identifying the transgressive segregants by selections in later generations.
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    ThesisItemOpen Access
    STUDIES ON GENETIC DIVERGENCE AND STABILITY OF LARGE SEEDED PEANUT (Arachis hypogaea L.)
    (Acharya N G Ranga Agricultural University, 2023-12-03) GALI SURESH; D. LOKANADHA REDDY
    The present investigation entitled “Studies on Genetic Divergence and Stability of Large Seeded Peanut (Arachis hypogaea L.)” was carried out in four seasons viz., kharif 2019, summer 2020, kharif 2020 and rabi 2020-21. Observations were recorded for kernel yield and its component traits in kharif 2019 to study the genetic divergence, genetic parameters, character association and direct and indirect effects of characters on kernel yield among 65 peanut genotypes. Among sixty five lines, twenty six lines were chosen for stability analysis across seasons namely, summer 2020, kharif 2020 and rabi 2020-21 to study G × E interaction. Analysis of variance (ANOVA) for yield and confectionery traits revealed highly significant differences among the genotypes for all characters studied in kharif, 2019. An analysis of genetic parameters reveled number of mature pods per plant, number of immature pods per plant, pod yield per plant, kernel yield per plant, 100 seed weight, free amino acids, total soluble sugars and oleic and linoleic acid ratio showed high variability (GCV and PCV), high heritability coupled with high genetic advance as per cent of mean, indicating the predominance of additive gene action in expression of these characters and direct selection will be effective in improvement of such characters. Diversity analysis showed that linoleic acid content contributed maximum variation to total variation. The 65 genotypes were divided into 10 clusters, with cluster IV having the highest number of genotypes (28) and clusters VI, VII and X had only single genotype. Maximum inter cluster D2 value was observed between cluster IX and cluster X. Cluster VI, VII, VIII, IX and X recorded high cluster mean values for most of the yield contributing and quality characters. PCA analysis revealed first five principal components PC 1 to PC 5 accounted more than 92 % of the entire variation and have latent roots greater than one. Results obtained from individual PCA (vectors X, Y, Z) and 3D plot graphed based on PCA loading scores (vectors X, Y, Z) of 65 peanut genotypes revealed that genotypes ICGV 03137 (cluster X), ICGV 171002 (cluster IX), ICGV 171004 (cluster IX) and ICGV 94215 (cluster VIII) were scattered relatively far away from other genotypes in this plot which indicates that they were more divergent and also confirming the Tocher‟s clustering. Intercrossing genotypes included in these clusters could be effective for creating variability in the respective traits. Character association revealed plant height, number of secondary branches per plant, number of mature pods per plant, number of immature pods per plant, pod yield per plant, 100 seed weight and protein content were recorded significant positive association with kernel yield per plant both at genotypic and phenotypic levels. On the other hand, character like days to 50 % flowering showed significant negative correlation with kernel yield per plant at phenotypic level but non-significant at genotypic level. Path coefficient analysis revealed number of mature pods per plant, 100 seed weight, number of secondary branches per plant and sound mature kernel per cent were leading in determining the kernel yield of peanut through direct positive effects and indirect positive effects via different yield attributing traits. Molecular diversity analysis revealed a total of 17 bands or DNA fragments found to be polymorphic and mean number of polymorphic bands per primer was 2.83. PIC values ranged from 0.423 for primer EM 18 to 0.742 for S 109 with an average of 0.572. The dendrogram analysis divided the total 65 genotypes into 10 diverse sub clusters. The grouping pattern of both PCA (4 groups) and PCoA (3 groups) very nearer to the dendrogram obtained through UPGMA based cluster analysis. The ANOVA of Eberhart and Russell model revealed significant differences among genotypes for all traits which indicates the presence of substantial variation in the per se performance of all the 26 peanut genotypes. Significant differences due to environments were observed for all traits except shelling percentage and palmitic acid content indicating that the environments in which the genotypes evaluated were quite variable. The environments + (genotypes × environments) interaction was also observed to be significant for all traits studied except for 100 seed weight and palmitic acid content indicating considerable interactions of genotypes with environments (seasons). Significant genotype × environment interactions (GEI) were recorded for all traits except for days to 50 % flowering, days to maturity and 100 seed weight which inferred that differential performance of peanut genotypes under diverse environments. Mean sum of squares due to environment (linear) were found to be significant for all traits except for palmitic acid content. Environmental index (I) revealed the fittingness of an environment for different traits of peanut. Plant height, number of primary branches per plant, number of secondary branches per plant, number of mature pods per plant, pod yield per plant, kernel yield per plant, sound mature kernel per cent and 100 seed weight were recorded higher positive values of environmental index in kharif season indicating that kharif season was congenial for most of the yield contributing traits than summer and rabi seasons. On the basis of stability parameters, none of the genotypes were stable for all the traits across the environments (seasons). Genotypes viz., ICGV 171334, ICGV 98432 and ICGV 99105 were observed to be stable across the seasons for high pod and kernel yield in conjunction with confectionary traits like 100 seed weight, protein content and oleic linoleic acid ratio.
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    ThesisItemOpen Access
    VALIDATION OF MOLECULAR MARKERS LINKED TO YMD RESISTANCE AND GENETIC ANALYSIS OF YIELD COMPONENTS IN BLACK GRAM [VIGNA MUNGO (L.) HEPPER]
    (Acharya N G Ranga Agricultural University, 2023-12-03) AYESHA MOHAMMED; D. RATNA BABU
    The present investigation was carried out with the chief objectives of assessing the role of different non-allelic interactions in the inheritance of various traits of black gram and to validate the reported molecular markers linked to YMD. Other parameters like mean, variability, heritability, expected genetic advance, correlation analysis, path coefficient analysis and divergence studies were also carried out for the 40 black gram germplasm lines. The required field experiments to achieve the targeted objectives were conducted at RARS, Lam, Guntur during 2019-20 and 2020-21 and the molecular biology experiments were carried out at Agricultural College, Bapatla during 2020-21. The analysis of variance indicated significant differences among the 40 genotypes for all the traits under study. High PCV and GCV were recorded for plant height, clusters per plant, pods per plant and grain yield per plant. The estimates of heritability and genetic advance as per cent of mean were high for the characters viz., plant height, clusters per plant, pods per plant, seed per pod and grain yield per plant indicating the probable operation of additive gene action in inheritance of these traits and simple selection is sufficient to improve these traits. Considering the nature and magnitude of character associations and their direct and indirect effects, it can be inferred that clusters per plant, pods per plant, seed per pod, pod length, test weight and days to maturity could serve as important traits in any selection programme for selecting high yielding genotypes in black gram. The D2 analysis grouped the 40 black gram genotypes into ten clusters. It revealed maximum divergence between clusters IV and IX, followed by clusters VIII and IX, clusters VII and IX and clusters II and IX suggesting that there is wide genetic diversity between these clusters. The genotypes from these clusters which are having better per se performance may result in superior transgressive segregants depending on the gene action. The PCA analysis identified that the maximum contributing traits towards the existing variability are days to 50% flowering, days to maturity, plant height, pod length, clusters per plant, grain yield per plant, branches per plant and seed per pod. It also revealed that the first three principal components contributed 79.592 per cent towards the total variability. Further, the diverse xvii genotypes PU 31, LBG 623, IPU 94-1, TU 94-2, GAVT 7, UAHS BG 1 and Vamban 8 which are far apart from each other in the two dimension and three dimension diagrams may result in good hybrid combinations to produce transgressive segregants in their respective F2 and subsequent segregating generations. The 40 germplasm lines phenotyped for YMD, exhibited high range of variation with respect to the disease reaction. Fifteen genotypes recorded no visible symptoms or even small yellow specks with restricted spread on foliage, indicating that they are resistant to yellow mosaic disease. These genotypes could be utilized as donors for transfer of disease resistance into agronomically superior genotypes which are lacking disease resistance. The results of generation mean analysis indicate that additive-dominant model is adequate only for one trait i.e. test weight. All other ten traits viz., days to 50% flowering, plant height, branches per plant, clusters per plant, pods per plant, pod length, seed per pod, days to maturity, grain yield per plant and reaction to YMD had significance for one or more scaling tests and also had significant Chi-square values of joint scaling tests. This clearly indicate the inadequacy of additive-dominant model to explain inheritance in these traits. Hence, the estimates of inter-allelic or non-allelic gene effects were obtained using six parameter model of generation mean analysis. In spite of having significant additive [d] and dominance [h] components, the non-allelic interactions overpowered them due to their higher estimates hence, had a great role in the inheritance of these ten traits. Inadequacy of additive-dominant model for explaining the inheritance of the ten out of eleven traits emphasizes the complex nature of gene effects suggesting that simple selection procedures may not be sufficient to improve the yield and its contributing traits. From the results of the studies pertaining to validation of molecular markers reported to be linked to YMD resistance, it was found that four reported markers viz., CYR 1, YR 4, DMB-SSR 158 and MYMVR-583 could only produce monomorphic bands and could not differentiate the resistant and susceptible genotypes. With regards to the remaining three molecular markers, it was found that they could only differentiate few lines as resistant or susceptible. And in considerable number of genotypes these markers did not co-segregated with the phenotype. There are many deviations from the expected amplification of the target fragment in both resistant and susceptible genotypes. This clearly suggest that these markers failed in differentiating resistant and susceptible genotypes. The claim made by the researchers that the reported markers (at least the three markers which are producing polymorphic bands) were linked to resistance, need not be differed as they have used mapping populations in developing these markers. However, there might be few more genes that are responsible for complete resistance against YMD and are need to be identified using mapping populations produced from parental lines having varying degree of genetic background. Further, the amplification of amplicons linked to resistant genes in phenotypically susceptible genotypes indicate that the marker is not tightly linked to the gene of interest and might be segregated and separated due to crossing over between the marker and the gene in question. Hence, to identify YMD resistant line, tightly linked markers for all the genes responsible for resistance need to be identified.
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    ThesisItemOpen Access
    STABILITY ANALYSIS IN SORGHUM [Sorghum bicolor (L.) Moench] GENOTYPES
    (guntur, 2022-08-17) KAVYA, PATI; SATYANARAYANA RAO, V.
    The present investigation was carried out at Agricultural College farm, Bapatla, Andhra Pradesh with the following objectives: Study of variability, diversity, correlation and path analysis, combining ability, stability analysis and generation mean analysis for 13 quantitative characters The data was recorded on Days to 50% flowering (Days), Days to maturity (Days), Plant height (cm), Number of nodes per plant, Stem girth (cm), Panicle weight (g), 1000 grain weight (g), Fresh stalk yield (T ha-1), Juice yield (l ha-1), Brix per cent, Total soluble sugars ( % ), Ethanol yield (l ha-1), Grain yield (T ha-1). The analysis of variance indicated significant differences among the 110 genotypes indicating the existence of variability among the genotypes. Estimates of PCV were narrowly higher than the corresponding GCV values for the characters days to 50 % flowering, days to maturity and stem girth, while number of nodes per plant, fresh stalk yield (t/ha), grain yield (t/ha), brix %, T.S.S, juice yield (t/ha), ethanol yield (t/ha) showed moderate differences between PCV and GCV. Characters plant height (cm), 1000 grain weight, Panicle weight (gm) showed high magnitude of difference. Narrow and moderate difference between PCV and GCV indicating less environment influence on these characters. Therefore, selection based on phenotypic performance could be worth in achieving desired results. High heritability coupled with high genetic advance as percent of mean was observed for all the 13 characters studied. The diversity study for 110 genotypes were grouped into 8 clusters indicating the presence of a wide range of genetic diversity. Cluster- I, was possessing the highest number of genotypes i.e., 78 indicating the genetic similarity among them followed by Cluster- III with 15 genotypes, Cluster - II with 12 genotypes. Cluster - IV, V, VI, VII, VIII were monogenotypic indicating the uniqueness of the genotypes included in those clusters when compared to other genotypes included in the study. The cluster means for brix %, juice yield, ethanol yield and days to 50 % flowering were considered as criteria and for crossing, diverse parents were selected from various clusters. i.e., from cluster IV, cluster V, cluster VI, cluster VII, and cluster VIII for hybridization programme. xvii The correlation results in 110 genotypes for 13 characters revealed that ethanol yield has significant positive correlation with brix percent, total soluble sugars, juice yield while negative association with grain yield, plant height, days to 50% flowering and days to maturity. Path coefficient analysis revealed that juice yield exerted the highest positive direct effect on ethanol yield followed by brix %, total sugar yield along with positive correlation for all the above mentioned characters. Four lines were crossed with 4 testers selected from the divergence studies in L x T fashion. The pooled analysis of variance for 13 characters measured over three locations in the present investigation revealed significant differences among environments, lines, testers, crosses, environment x line x tester for all the characters studied except panicle weight. In the line x tester analysis, sca variance component estimates were greater than that of gca for the characters no of nodes, fresh stalk yield (t/ha),stem girth (cm), 1000 grain weight (g), panicle weight(g), brix%, total soluble sugars, juice yield(l/ha) and grain yield(t/ha) indicating the non-additive control of genetic variation in these traits. Female line 1 (ICSA-14029) was found to be promising general combiner for fresh stalk yield, brix%, total soluble sugars, juice yield, and ethanol yield with higher positive significant GCA effects, while line 4 (ICSA-14035) was negative significant for all the characters studied except stem girth and plant height indicating this line was poor combiner for all the characters. Among the testers which are used as male parents, tester 3 (ICSV 15006) has shown positive significant gca for all the traits like number of nodes, plant height, fresh stalk weight, stem girth, panicle weight, brix per cent, total soluble sugars, juice yield, ethanol yield followed by tester 2 (GGUB 28) possessing positive gca for juice yield and ethanol yield and tester 4 (IS 29308) had positive significant gca for brix %, total soluble sugars. Tester 1 (SEVS-08) recorded negative significant association for brix, total soluble solids, juice yield, ethanol yield and grain yield. Among the hybrids, hybrid ICSA 14029 x ICSV 15006 has excelled with high sca effects for brix%, total soluble sugars, juice yield and ethanol yield followed by hybrid ICSA 14029 x GGUB 28 having high sca effects for brix %, total soluble sugars, juice yield and ethanol yield, 1000 grain weight, panicle weight. Hybrid ICSA 14030 x IS 29308 showed high sca effects for brix, total soluble sugars, juice yield, ethanol yield, days to maturity, 1000 grain weight, panicle weight and negative significant for no. of nodes, days to 50 % flowering, fresh stalk yield, stem girth. Hybrid ICSA 14033 x SEVS-08 was possessing high sca effects for brix, total soluble sugars, juice yield and ethanol yield,1000 grain weight, days to 50% flowering and Number of nodes and negative effects for days to maturity, fresh stalk yield, stem girth and hybrid ICSA 14035 x SEVS-08 showing significant sca effects for juice and ethanol yield respectively. Among the Hybrids H-3, H-2, H-8 and H-10 were found to be superior for juice, brix percent and ethanol content. Hence the following hybrids can be used for further improvement. The range of heterosis over mid parent, better parent and commercial check indicated that it was high with respect to ethanol productivity related traits particularly juice yield and brix per cent. Considering standard heterosis as reference point for viz; xviii juice yield, brix and ethanol yields the following hybrids have performed well ICSA 14029 x ICSV-15006; ICSA 14030 x ICSV 15006; ICSA 14305 x ICSV-15006; ICSA 14029 x GGUB 28; ICSA 14030 x GGUB 28; ICSA 14033 x ICSV-15006. Stability analysis was conducted for 16 F1 hybrids at three different locations. In pooled analysis of variance for stability, the genotypes, environments, genotype-environment interaction, environment (linear) and pooled deviations showed significant differences for most of the characters studied. Stability analysis through “Eberhart and Russell’s model” resulted that Bapatla location was found to be most favourable location for brix %, total soluble sugars, ethanol yield and seed yield. Guntur was the most favourable location for number of nodes per plant and juice yield. Garikapadu was the favourable for days to fifty percent flowering, days to maturity, plant height, fresh stalk yield, stem girth, 1000 grain weight and panicle weight. According to AMMI analysis the following hybrids were stable over locations for these characters like H-2 for days to 50% flowering, H-3 and H-5 for days to maturity, H-10 and H-2 for plant height, H-7 and H-5 for no of nodes per plant, H-15 for stem girth, H-3 and H-4 for 1000 grain weight, H-5 for fresh stalk yield , hybrids 12, 10,11, 2 for grain yield, H -7 for brix%, H- 7 & H-8 for total soluble sugars and H-10 and 11 for juice yield and H-2 and 3 for ethanol yield. The classification for Eberhart and Russell’s model and AMMI model was similar for the traits Days to 50% flowering, days to maturity, Plant height, number of nodes per plant. For remaining characters the AMMI classification doesn’t present any similarity with the results obtained by Eberhart and Russell’s model. The stable performing hybrids ICSA 14029 x GGUB 28, ICSA 14035 x GGUB 28 and ICSA 14033 x IS 29308 which are tested in 3 locations may be further tested in All India trials before commercial expoliatation of ethanol production. In the generation mean analysis study of ICSB 14029 x ICSV 15006, mean performance of 6 populations indicated that the F2 means were lesser than the F1 means except for brix per cent and stem girth and between mid-parental values in respect of all the traits except panicle weight, fresh stalk weight, grain yield indicating high degree of inbreeding depression. These results depict the predominant role of non-additive gene action which includes both dominance as well as epistatic interactions. The scaling tests as well as chi square test from joint scaling test were highly significant in the cross ICSB 14029 x ICSV 15006’ cross for 11 characters excluding stem girth and 1000 grain weight, indicating inadequacy of simple additive-dominance model and justifying the use of six parameter model for the detection of gene interactions. The six generation mean analysis carried out for 13 quantitative characters indicated significance of dominance gene effects for days to flowering, plant height, fresh stalk weight, juice yield, grain yield and ethanol yield. Significance of one or more interaction types (additive × additive or additive × dominance or dominance × dominance) in all the 13 traits except nodes per plant, stem girth, 1000 grain weight, total sugars estimation and ethanol yield was observed. Based on the signs of [hˆ] and [lˆ] gene effects, complementary gene interaction was evident in the inheritance of days to 50% flowering, days to maturity, juice yield, ethanol yield, while, duplicate gene xix interaction in the inheritance was evident for plant height, number of nodes per plant, stem girth, panicle weight, 1000 grain weight, fresh stalk weight, brix %, total sugars estimation, grain yield indicating predominantly dispersed alleles at the interacting loci.
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    ThesisItemOpen Access
    GENETIC DISSECTION OF SEEDLING AND REPRODUCTIVE STAGE SALINITY TOLERANCE IN RICE USING SALT TOLERANT CULTIVAR MTU 1061
    (guntur, 2022-08-11) VIJAYA DURGA, K.; SATYANARAYANA, P. V.
    The present investigation was undertaken with an aim to identify salinity tolerance lines in F2 population through phenotyping (seedling and reproductive stages) and genotyping (detect presence of salt tolerance QTLs). The present study entitled “Genetic Dissection of Seedling and Reproductive Stage Salinity Tolerance in Rice Using Salt Tolerant Cultivar MTU 1061” was conducted at Regional Agricultural Research Station, Maruteru, with main objective of development and genotyping of mapping population (234 F2 lines) to identify the chromosomal regions relating to seedling and reproductive stage salinity tolerance and phenotyping of the 234 F2:3 progenies for seedling and reproductive stage salinity tolerance. 234 F2:3 lines derived from a cross between a high yielding salt susceptible rice cultivar Sri Druthi (MTU 1121) and salt tolerant variety Indra (MTU 1061) were evaluated for salt tolerance at both stages namely seedling and reproductive stages using hydroponics and pot culture experiment respectively under salinity stress (EC @ 6 and 12 dSm-1). Data on seven seedling salinity tolerance traits viz., salt injury score (SIS), shoot Na+ concentration, shoot K+ concentration, Na/K ratio, shoot length (cm), root length (cm), shoot dry weight (g) and eight yield contributing traits viz., plant height at maturity, days to flowering, panicle length, number of filled grains per panicle, number of total grains per panicle, spikelet fertility, grain yield/plant and productive tillers per plant were recorded. xvii A set of 234 F2:3 lines were evaluated for salt tolerance at seedling stage in a hydroponics experiment taken up during Rabi 2018-19 and Kharif 2019. The F2:3 population and parents showed a wide range of variation for different morpho-physiological traits in response to salt stress. Based on modified standard evaluation score (1-9) for visual salt injury at seedling stage, one line was highly tolerant, forty were tolerant, one hundred fifteen were moderately tolerant, seventy-one were susceptible and the rest seven were highly susceptible. Whereas, donor parent MTU 1061 showed tolerant (score of 3) and recipient parent MTU 1121 showed susceptible reaction (score of 9). In F2:3, shoot Na+ concentration, shoot K+ concentration, Na/K ratio, shoot length (cm), root length (cm) and shoot dry weight (g) ranged from 11.39 ppm to 40 ppm, 4.52 ppm to 17.94 ppm, 1.50 to 5.00, 6.58 cm to 30.59 cm, 6.42 cm to 19.00 cm and 0.07 g to 2.31 g, respectively. In this study, at seedling stage the F2:3 lines had high Na+ and high K+ concentration in the shoot suggesting that homeostasis between Na+ and K+ plays a key role in the seedling stage tolerance to salt stress. Screening of 234 F2:3 lines at reproductive stage was taken up during Rabi 2019-20 using pot culture experiment. Parents and the F2:3 population showed a high variation for different evaluated yield traits in response to salt stress (EC @ 12 dS/m). Grain yield per plant is the best indicative score for tolerance at reproductive stage. Out of the 234 F2:3 lines, five were highly tolerant (grain yield/plant >2.5 g), forty-five were tolerant (grain yield/plant 1.5 g – 2.5 g) and the rest one hundred eighty-four were susceptible (grain yield/plant <1.5 g). Whereas, donor parent MTU 1061 was highly tolerant (grain yield/plant 2.83 g) and recipient parent MTU 1121 showed susceptible reaction (grain yield/plant 0.72 g). In F2:3, plant height, days to flowering, panicle length, number of filled grains per panicle, number of total grains per panicle, spikelet fertility, productive tillers per plant ranged from 46 cm to 102 cm, 92 to 106, 14 cm to 22 cm, 10 to 296, 116 to 459, 6 to 73 and 2 to 5, respectively. In seedling and reproductive stages, a total of 234 F2:3 lines derived from MTU 1061 / MTU 1121 were evaluated for salinity tolerance. Out of the 234 F2:3 lines only seven lines were tolerant in both stages i.e., in seedling stage based on SIS and NaK ratio, in reproductive stage based on grain yield / plant. The selected lines with salinity tolerance at both the stages will be further advanced and will be evaluated in yield trials under stress and non stress conditions. And selected tolerant F2:3 lines (seven lines) will be valuable material for further fine mapping and introgression into elite genotypes to develop salt tolerant varieties. To identify the chromosomal regions relating to seedling and reproductive stages salinity tolerance, the F2 mapping population (234 F2 lines) was developed by making cross between MTU 1061 (donor) and MTU 1121 (recipient). The two parental lines MTU 1061 and MTU 1121 were screened for parental polymorphism using 1,001 SSR markers spanning all the 12 chromosomes. Among 1,001 SSR markers, 104 markers (10%) were xviii polymorphic. The molecular linkage map was constructed using 104 polymorphic markers spanning a total map length of 2956.12 cM using kosambi mapping function using IciMapping V.4.1 software. QTL mapping was carried out using Interval Mapping (IM), Inclusive Composite Interval Mapping (ICIM) and Interval Mapping for Epistatic Mapping (IM-EPI) methods in both seedling and reproductive stages. QTL analyses were conducted for seven seedling salinity tolerance traits in the F2:3 population using interval mapping (IM) and inclusive composite interval mapping (ICIM). A total of 49 additive QTLs were detected by IM for all seven traits whereas 51 additive QTLs were detected by ICIM. A total of 257 pairs of interactive epistatic QTLs were detected by Interval Mapping for Epistatic Mapping (IM-EPI) method. Forty-nine QTLs detected in IM were same as with ICIM. In both methods (IM and ICIM), out of the 49 QTLs, two novel QTLs for SIS score, four QTLs for shoot Na+ concentration, two QTLs for shoot K+ concentration, 16 QTLs for NaK ratio, 17 QTLs for shoot length, six QTLs for root length and two QTLs for shoot dry weight were detected with phenotypic variance ranging from 0.1% to 11%. Compared to IM method, extra two QTLs (qDWT-6-1 and qDWT-9-1) detected for shoot dry weight on chromosomes 6 and 9 in ICIM method. qDWT-6-1 which had a phenotypic variance of 11% and this QTL was detected in the region between RM50 – RM3431 on chromosome 6 which had LOD ≥ 2. In IM-EPI method, 257 pairs of interactive epistatic QTLs were detected, out of 257 pairs of epistatic QTLs, 32 pairs of QTLs for SIS score, 21 pairs of QTLs for shoot Na+ concentration, 15 pairs of QTLs for shoot K+ concentration, 52 pairs of QTLs for NaK ratio, 60 pairs of QTLs for shoot length, 72 pairs of QTLs for root length, five pairs of QTLs for shoot dry weight. One hundred and ten epistatic QTLs were co-localized with 39 additive QTLs for seven seedling salinity tolerant traits. Among salinity tolerance traits, Na+/K+ ratio, an important ion balancing parameter for the salt tolerance, was controlled by 16 QTLs were mapped on chromosomes 1, 3, 4, 6, 7, 8, 9, 10 and 12 detected by IM and ICIM. All QTLs were with small effects with phenotypic variance ranging from 0.5% to 1%. Out of the 16 QTLs, one of the QTL qNaK-1-1 position was corresponding to Saltol locus on chromosome 1. QTL analyses were conducted for eight yield contributing traits under reproductive stage salinity in the F2:3 population using interval mapping (IM) and inclusive composite interval mapping (ICIM). A total of 32 additive QTLs were detected by IM for all eight traits whereas 25 additive QTLs were detected by ICIM. A total of 201 pairs of interactive epistatic QTLs were detected by Interval Mapping for Epistatic Mapping (IM-EPI) method. Twenty-five QTLs detected in ICIM were same as with IM. Out of 25 QTLs, two QTLs for plant height, two QTLs for days to flowering, seven QTLs for number of filled grains per panicle, two QTLs for number of total grains per panicle, three QTLs for spikelet fertility, seven QTLs for grain yield per plant and two QTLs for productive tillers per plant. Compared to ICIM method, additional seven QTLs were detected in IM method, five QTLs (qDFL-6-1, qDFL-6-2, qDFL-7- xix 1, qDFL-9-2 and qDFL-11-1) for days to flowering, one QTL (qGY-12-1) for grain yield per plant and one QTL (qPT-12-1) for productive tillers per plant. All additive QTLs were minor with a phenotypic variance ranging from 0.2% to 7% detected by IM and ICIM. In IM-EPI method, 201 pairs of interactive epistatic QTLs were detected, out of 201 pairs of epistatic QTLs, eight pairs of QTLs for plant height, 35 pairs of QTLs for days to flowering, five pairs of QTLs for panicle length, 43 pairs of QTLs for number of filled grains per panicle, eight pairs of QTLs for number of total grains per panicle, 38 pairs of QTLs for spikelet fertility, 42 pairs of QTLs for grain yield per plant and 22 pairs of QTLs for productive tillers per plant. Forty-nine epistatic QTLs were co-localized with 19 additive QTLs for six reproductive salinity tolerant traits. At seedling stage, the phenotypic responses, genomic composition, and QTLs identified from the study indicated that Na/K ratio is the key factor for salinity tolerance. The mechanisms of tolerance might be due to homeostasis between Na+ and K+ or Na+ compartmentation. In reproductive stage phenotypic responses and QTLs identification indicated that grain yield per plant under stress is the key factor comparative to remaining parameters such as number of spikelets, filled spikelets and unfilled spikelets. It can be concluded from the study that tolerance at the seedling stage is not necessarily associated with tolerance at the reproductive stage and vice versa. The tolerant F2:3 lines will be a valuable pre-breeding material for use in rice breeding programs and also provide an opportunity for functional genomics studies to provide molecular insights into salt tolerance mechanisms in MTU 1061.