S. Rahangdale, Y. Singh, P. K. Upadhyay, G. K. Koutu
In present study, 67 JNPT (Jawahar New Plant Type) lines were evaluated for 28 morphological and quality traits planted in RCBD with three replications. Principal Component Analysis (PCA) revealed that out of 28, only eight PCs exhibited more than 1.0 eigen value and showed about 81.84% total variability. For selecting the high yielding genotypes in rice, the characters viz., spikelet density, spikelet fertility, number of tillers plant–1and panicle weight plant–1 may be considered. On the basis of high PC score ten most prominent lines namely JNPT-1059-9, JNPT-1059- 10, JNPT1062-1, JNPT-1062-2, JNPT-1064-9, JNPT-1065-1, JNPT-1065-2, JNPT1065-3, JNPT-1066-52 and JNPT-1068- 65 were identified for yield and quality traits.
本研究对67个JNPT (Jawahar New Plant Type)品系在RCBD上进行了3个重复的28个形态和品质性状的评价。主成分分析(PCA)表明，28个样本中只有8个样本的特征值大于1.0，变异率约为81.84%。在选择水稻高产基因型时，可考虑小穗密度、小穗育性、分蘖数和穗重等性状。在PC得分较高的基础上，鉴定了产量和品质性状最突出的10个品系:JNPT-1059-9、JNPT-1059- 10、JNPT1062-1、JNPT-1062-2、JNPT-1064-9、JNPT-1065-1、JNPT-1065-2、JNPT1065-3、JNPT-1066-52和JNPT-1068- 65。
{"title":"Principal component analysis of JNPT lines of rice for the important traits responsible for yield and quality","authors":"S. Rahangdale, Y. Singh, P. K. Upadhyay, G. K. Koutu","doi":"10.31742/ijgpb.81.1.14","DOIUrl":"https://doi.org/10.31742/ijgpb.81.1.14","url":null,"abstract":"In present study, 67 JNPT (Jawahar New Plant Type) lines were evaluated for 28 morphological and quality traits planted in RCBD with three replications. Principal Component Analysis (PCA) revealed that out of 28, only eight PCs exhibited more than 1.0 eigen value and showed about 81.84% total variability. For selecting the high yielding genotypes in rice, the characters viz., spikelet density, spikelet fertility, number of tillers plant–1and panicle weight plant–1 may be considered. On the basis of high PC score ten most prominent lines namely JNPT-1059-9, JNPT-1059- 10, JNPT1062-1, JNPT-1062-2, JNPT-1064-9, JNPT-1065-1, JNPT-1065-2, JNPT1065-3, JNPT-1066-52 and JNPT-1068- 65 were identified for yield and quality traits.","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43323743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Sanwal, A. Mann, Hari Kesh, G. Kaur, Raj Kumar, A. Rai
Twenty four Okra genotypes were evaluated for marketable fruit yield and its related traits for genotype environment interaction during 2015-16 and 2016-17. The genotypes were exposed to alkaline environment with a pH range of 8.0±0.2, 8.5±0.2, 9.0±0.2 and 9.5±0.2. A significant level of deviation in expression of different traits was observed in all the genotypes with increasing pH. Based on Additive Main Effects and Multiplicative Interaction (AMMI), Genotype and Genotype Environment Interaction (GGE) biplot, Wrick’s ecovalence (Wi2 ), AMMI Stability Value (ASV) and Yield Stability Index (YSi) stable genotypes with high fruit yield were identified over the eight environments. The combined AMMI analysis of variance indicated that genotype main effect, environment and genotype-by-environment interaction effects showed variation of 19.83%, 63.07% and 17.10%, respectively for fruit yield. On the basis of different stability measures, VRO-112, VRO-110, Kashi Kranti, VROB178, AE-70 and VRO-108 were differentiated as high yielding and stable genotypes over the tested environments. This study will be helpful for selecting alkali tolerant okra parents for further breeding programme and recommending the suitable genotypes for alkalinity prone area
{"title":"Genotype environment interaction analysis for fruit yield in okra (Abelmoschus esculentus L.) under alkaline environments","authors":"S. Sanwal, A. Mann, Hari Kesh, G. Kaur, Raj Kumar, A. Rai","doi":"10.31742/ijgpb.81.1.11","DOIUrl":"https://doi.org/10.31742/ijgpb.81.1.11","url":null,"abstract":"Twenty four Okra genotypes were evaluated for marketable fruit yield and its related traits for genotype environment interaction during 2015-16 and 2016-17. The genotypes were exposed to alkaline environment with a pH range of 8.0±0.2, 8.5±0.2, 9.0±0.2 and 9.5±0.2. A significant level of deviation in expression of different traits was observed in all the genotypes with increasing pH. Based on Additive Main Effects and Multiplicative Interaction (AMMI), Genotype and Genotype Environment Interaction (GGE) biplot, Wrick’s ecovalence (Wi2 ), AMMI Stability Value (ASV) and Yield Stability Index (YSi) stable genotypes with high fruit yield were identified over the eight environments. The combined AMMI analysis of variance indicated that genotype main effect, environment and genotype-by-environment interaction effects showed variation of 19.83%, 63.07% and 17.10%, respectively for fruit yield. On the basis of different stability measures, VRO-112, VRO-110, Kashi Kranti, VROB178, AE-70 and VRO-108 were differentiated as high yielding and stable genotypes over the tested environments. This study will be helpful for selecting alkali tolerant okra parents for further breeding programme and recommending the suitable genotypes for alkalinity prone area","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47494346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Buckwheat has attracted considerable interest amongst the global scientific community due to its nutritional and pharmaceutical properties. It is a low input crop whose cultivation has persisted through centuries of civilization in almost every country where cereals were cultivated. The crop is an important source of rutin, an important flavonoid which is known to have cardioprotective, vasoprotective, antihypertensive, anti-inflammation, cytoprotective and anti-diabetic properties. Grains of buckwheat are a rich source of protein with a balanced amino acid composition, gluten free flour, dietary fibre, vitamins, resistant starch, phytosterols, fagopyrins, fagopyritols and phenolic compounds. Buckwheat is a short season crop which completes its life cycle in 70-90 days and can grow in wide range of environmental conditions including marginal lands and rocky, poorly tilled soils. The protein content in buckwheat flour is higher than in commonly used cereals such as rice, wheat, millet, sorghum and maize. Buckwheat grain protein is rich in lysine and arginine, which are generally limiting in other cereals. Because of a low Lys/ Arg and Met/Gly ratio, buckwheat protein has strong hypolipidemic activity. While Buckwheat is considered as a healthy food because of its nutraceutical properties, low yields due to seed shattering because of pedicel breaking and heterozygosity due to self-incompatibility as a consequence of dimorphic heterostylism have always remained major problems in achieving large scale incorporation of common buckwheat (Fagopyrum esculentum) in the agricultural portfolio. The present review highlights the multicore potential of buckwheat as a super crop to meet the challenges of food and nutritional security.
{"title":"Buckwheat: A critical approach towards assessment of its potential as a super crop","authors":"N. Chrungoo, Upasna Chettry","doi":"10.31742/ijgpb.81.1.1","DOIUrl":"https://doi.org/10.31742/ijgpb.81.1.1","url":null,"abstract":"Buckwheat has attracted considerable interest amongst the global scientific community due to its nutritional and pharmaceutical properties. It is a low input crop whose cultivation has persisted through centuries of civilization in almost every country where cereals were cultivated. The crop is an important source of rutin, an important flavonoid which is known to have cardioprotective, vasoprotective, antihypertensive, anti-inflammation, cytoprotective and anti-diabetic properties. Grains of buckwheat are a rich source of protein with a balanced amino acid composition, gluten free flour, dietary fibre, vitamins, resistant starch, phytosterols, fagopyrins, fagopyritols and phenolic compounds. Buckwheat is a short season crop which completes its life cycle in 70-90 days and can grow in wide range of environmental conditions including marginal lands and rocky, poorly tilled soils. The protein content in buckwheat flour is higher than in commonly used cereals such as rice, wheat, millet, sorghum and maize. Buckwheat grain protein is rich in lysine and arginine, which are generally limiting in other cereals. Because of a low Lys/ Arg and Met/Gly ratio, buckwheat protein has strong hypolipidemic activity. While Buckwheat is considered as a healthy food because of its nutraceutical properties, low yields due to seed shattering because of pedicel breaking and heterozygosity due to self-incompatibility as a consequence of dimorphic heterostylism have always remained major problems in achieving large scale incorporation of common buckwheat (Fagopyrum esculentum) in the agricultural portfolio. The present review highlights the multicore potential of buckwheat as a super crop to meet the challenges of food and nutritional security.","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49019065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Prem Chand Gyani, H. Bollinedi, S. G. Krishnan, K. Vinod, P. Bhowmick, M. Nagarajan, N. Singh, R. Ellur, Ashok K. Singh
Phytic acid (PA) acts as chelator of cationic mineral elements iron (Fe) and zinc (Zn) and obstructs their absorption in the human gut. We have evaluated a set of 162 traditional rice landraces for phytic acid phosphorus (PA-P), inorganic phosphorus (Pi) and total phosphorus (TP). Wide variability was observed for PA-P, Pi and TP ranging from 1.12 to 3 mg/g, 0.004 to 0.16 mg/g and 1.17 to 3.04 mg/g respectively. The mineral micronutrients, Fe and Zn were not in correlation with PA-P, Pi and TP implicating the possibility of their independent improvement while PAP showed a significant positive correlation with TP and significant negative correlation with Pi. Principal component analysis (PCA) identified two principal components PC1 and PC2, explaining 50.6 % and 32.1 % of the total variation, respectively. Cluster analysis grouped the accessions into four clusters. The study has also led to the identification of promising donors such as P1490 and Gowri with low PA content to be utilized in rice biofortification programmes.
{"title":"Characterizing the diversity of grain phytic acid content in Indian rice landraces by multivariate genetic analyses","authors":"Prem Chand Gyani, H. Bollinedi, S. G. Krishnan, K. Vinod, P. Bhowmick, M. Nagarajan, N. Singh, R. Ellur, Ashok K. Singh","doi":"10.31742/ijgpb.81.1.3","DOIUrl":"https://doi.org/10.31742/ijgpb.81.1.3","url":null,"abstract":"Phytic acid (PA) acts as chelator of cationic mineral elements iron (Fe) and zinc (Zn) and obstructs their absorption in the human gut. We have evaluated a set of 162 traditional rice landraces for phytic acid phosphorus (PA-P), inorganic phosphorus (Pi) and total phosphorus (TP). Wide variability was observed for PA-P, Pi and TP ranging from 1.12 to 3 mg/g, 0.004 to 0.16 mg/g and 1.17 to 3.04 mg/g respectively. The mineral micronutrients, Fe and Zn were not in correlation with PA-P, Pi and TP implicating the possibility of their independent improvement while PAP showed a significant positive correlation with TP and significant negative correlation with Pi. Principal component analysis (PCA) identified two principal components PC1 and PC2, explaining 50.6 % and 32.1 % of the total variation, respectively. Cluster analysis grouped the accessions into four clusters. The study has also led to the identification of promising donors such as P1490 and Gowri with low PA content to be utilized in rice biofortification programmes.","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46814272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. K. Naidu, S. K. Pattanashetti, Omesh Kumar, O. Sridevi, Basanagouda C Patil
Groundnut is sensitive to Fe deficiency under alkaline and calcareous soils and exhibits iron deficiency chlorosis (IDC) causing significant reduction in growth and yield. Genotypes were assessed for IDC related traits such as visual chlorosis rating, SPAD chlorophyll meter reading, chlorophyll and active iron (Fe2+) content across five growth stages and also for productivity traits viz., plant height, number of primary branches, number of pods per plant, pod yield, shelling per cent, 100 seed weight and haulm yield. Comparison between Fe-supplemented and Fe-nonsupplemented condition for IDC related traits showed not much difference among IDC tolerant genotypes across all five growth stages, while significant differences among IDC susceptible genotypes were observed. Maximum reduction in pod yield was observed among IDC susceptible genotypes compared to IDC tolerant and moderately tolerant genotypes. However, recently released variety G 2- 52 with moderate tolerance to IDC and higher yield potential recorded higher pod yield both under Fe applied (1754 kgha–1) and non-applied conditions (1544 kgha–1).
{"title":"Differential response of groundnut genotypes for iron (Fe) deficiency chlorosis tolerance and productivity traits under Fe-supplemented and Fe-non-supplemented conditions","authors":"G. K. Naidu, S. K. Pattanashetti, Omesh Kumar, O. Sridevi, Basanagouda C Patil","doi":"10.31742/ijgpb.81.1.8","DOIUrl":"https://doi.org/10.31742/ijgpb.81.1.8","url":null,"abstract":"Groundnut is sensitive to Fe deficiency under alkaline and calcareous soils and exhibits iron deficiency chlorosis (IDC) causing significant reduction in growth and yield. Genotypes were assessed for IDC related traits such as visual chlorosis rating, SPAD chlorophyll meter reading, chlorophyll and active iron (Fe2+) content across five growth stages and also for productivity traits viz., plant height, number of primary branches, number of pods per plant, pod yield, shelling per cent, 100 seed weight and haulm yield. Comparison between Fe-supplemented and Fe-nonsupplemented condition for IDC related traits showed not much difference among IDC tolerant genotypes across all five growth stages, while significant differences among IDC susceptible genotypes were observed. Maximum reduction in pod yield was observed among IDC susceptible genotypes compared to IDC tolerant and moderately tolerant genotypes. However, recently released variety G 2- 52 with moderate tolerance to IDC and higher yield potential recorded higher pod yield both under Fe applied (1754 kgha–1) and non-applied conditions (1544 kgha–1).","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46560533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Ajay, K. Ramya, R. A. Fiyaz, G. Govindaraj, S. Bera, N. Kumar, K. Gangadhar, Praveen Kona, G. P. Singh, T. Radhakrishnan
Outliers are a common phenomenon when genotypes are evaluated over locations and years under field conditions and such outliers makes studying genotype-environment Interactions difficult. Robust-AMMI models which use a combination of robust fit and robust SVD approaches, denoted as ‘R-AMMI-RLM’ have been proposed to study GEI in presence of such outliers. Instead of ‘R-AMMI-RLM’ we propose a model which uses a combination of linear fit and robust SVD to study GEI in presence of outliers and we denote this model as ‘R-AMMI-LM’. Here we prove that ‘RAMMI-LM’ was superior over ‘R-AMMI-RLM’ as it recorded very low residual sum of squares and low RMSE values. Thus proposed, ‘R-AMMI-LM’ model could explain the GEI more precisely even in presence of outliers.
{"title":"R-AMMI-LM: Linear-fit Robust-AMMI model to analyze genotype-by environment interactions","authors":"B. Ajay, K. Ramya, R. A. Fiyaz, G. Govindaraj, S. Bera, N. Kumar, K. Gangadhar, Praveen Kona, G. P. Singh, T. Radhakrishnan","doi":"10.31742/ijgpb.81.1.9","DOIUrl":"https://doi.org/10.31742/ijgpb.81.1.9","url":null,"abstract":"Outliers are a common phenomenon when genotypes are evaluated over locations and years under field conditions and such outliers makes studying genotype-environment Interactions difficult. Robust-AMMI models which use a combination of robust fit and robust SVD approaches, denoted as ‘R-AMMI-RLM’ have been proposed to study GEI in presence of such outliers. Instead of ‘R-AMMI-RLM’ we propose a model which uses a combination of linear fit and robust SVD to study GEI in presence of outliers and we denote this model as ‘R-AMMI-LM’. Here we prove that ‘RAMMI-LM’ was superior over ‘R-AMMI-RLM’ as it recorded very low residual sum of squares and low RMSE values. Thus proposed, ‘R-AMMI-LM’ model could explain the GEI more precisely even in presence of outliers.","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44765686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stem characters such as stem solidness and stem carbohydrates (water soluble carbohydrates and non-structural carbohydrates estimated as fructan) play an important role in stabilizing grain yield in stressful environments. Ten wheat genotypes were screened for carbohydrate content (Water soluble sugars and fructan) in peduncle along with other stem parameters namely, stem solidness, grain growth rate and stem osmotic potential under irrigated and drought conditions. Data was analyzed for correlation among these parameters along with biomass and yield. The results of present study indicated that stress-tolerant genotype RIL-S1-38 and WH 1235 accumulated higher fructan content in stem and contributed in grain growth rate, reduced osmotic potential and further imparted drought tolerance. Clear differences in stem solidness and fructan content exhibited lesser grain yield reduction under drought condition.
{"title":"Genetic variation of stem characters in wheat and their relation to physiological characters and yield under drought","authors":"Pooja, Sônia, R. Munjal, Suresh","doi":"10.31742/ijgpb.80.4.1","DOIUrl":"https://doi.org/10.31742/ijgpb.80.4.1","url":null,"abstract":"Stem characters such as stem solidness and stem carbohydrates (water soluble carbohydrates and non-structural carbohydrates estimated as fructan) play an important role in stabilizing grain yield in stressful environments. Ten wheat genotypes were screened for carbohydrate content (Water soluble sugars and fructan) in peduncle along with other stem parameters namely, stem solidness, grain growth rate and stem osmotic potential under irrigated and drought conditions. Data was analyzed for correlation among these parameters along with biomass and yield. The results of present study indicated that stress-tolerant genotype RIL-S1-38 and WH 1235 accumulated higher fructan content in stem and contributed in grain growth rate, reduced osmotic potential and further imparted drought tolerance. Clear differences in stem solidness and fructan content exhibited lesser grain yield reduction under drought condition.","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44761625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Neeraj Budhlakoti, Anil Rai, D. Mishra, S. Jaggi, Mukesh Kumar, A. Rao
Genomic Selection (GS) is the most prevalent method in today’s scenario to access the genetic merit of individual under study. It selects the candidates for next breeding cycle on the basis of its genetic merit. GS has successfully been used in various plant and animal studies in last decade. Several parametric statistical models have been proposed and being used successfully in various GS studies. However, performance of parametric methods becomes very poor when we have non additive kind of genetic architecture. In such cases, generally performance of non-parametric methods are quite satisfactory as these methods do not require strict statistical assumptions. This article presents comparative performance of few most commonly used non-parametric methods for complex genetic architecture i.e. non-additive, using simulated dataset generated at different level of heritability and varying combination of population size. Among several non-parametric methods, SVM outperformed across a range of genetic architecture.
{"title":"Comparative study of different non-parametric genomic selection methods under diverse genetic architecture","authors":"Neeraj Budhlakoti, Anil Rai, D. Mishra, S. Jaggi, Mukesh Kumar, A. Rao","doi":"10.31742/ijgpb.80.4.4","DOIUrl":"https://doi.org/10.31742/ijgpb.80.4.4","url":null,"abstract":"Genomic Selection (GS) is the most prevalent method in today’s scenario to access the genetic merit of individual under study. It selects the candidates for next breeding cycle on the basis of its genetic merit. GS has successfully been used in various plant and animal studies in last decade. Several parametric statistical models have been proposed and being used successfully in various GS studies. However, performance of parametric methods becomes very poor when we have non additive kind of genetic architecture. In such cases, generally performance of non-parametric methods are quite satisfactory as these methods do not require strict statistical assumptions. This article presents comparative performance of few most commonly used non-parametric methods for complex genetic architecture i.e. non-additive, using simulated dataset generated at different level of heritability and varying combination of population size. Among several non-parametric methods, SVM outperformed across a range of genetic architecture.","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44899902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Akhtar, D. Gautam, R. Nath, A. Gaikwad, K. V. Bhat, B. Mondal, G. Jat, Asif Iquebal, Badrish Tiwari, S. Archak
This study was undertaken to identify new sources of resistance against downy mildew of cucumber caused by Pseudoperonospora cubensis [(Berk. and Cart.) Rostow]. Pot experiments were conducted with 16 accessions each of Cucumis sativus and C. hardwickii during the years 2017 and 2018 using 12 isolates of P. cubensis representing different agroclimatic zones of India. The accession, IC331627 from Dehradun, Uttarakhand showed plant disease index (PDI) ranging from 5.55-20.35 per cent with an average PDI of 11.56 and 11.87 per cent during the years, 2017 and 2018, respectively. Hence, IC331627 was identified to be resistant against the five isolates of P. cubesis (Pc12, Pc17, Pc19, Pc21 and Pc24) and moderately resistant against one isolate (Pc22). This resistant accession C. hardwickii (IC331627) could be utilized to develop mapping population to map genomic regions conferring the resistance to downy mildew in cucumber.
{"title":"Identification of new resistant sources against downy mildew disease from a selected set of cucumber germplasm and its wild relatives","authors":"J. Akhtar, D. Gautam, R. Nath, A. Gaikwad, K. V. Bhat, B. Mondal, G. Jat, Asif Iquebal, Badrish Tiwari, S. Archak","doi":"10.31742/ijgpb.80.4.8","DOIUrl":"https://doi.org/10.31742/ijgpb.80.4.8","url":null,"abstract":"This study was undertaken to identify new sources of resistance against downy mildew of cucumber caused by Pseudoperonospora cubensis [(Berk. and Cart.) Rostow]. Pot experiments were conducted with 16 accessions each of Cucumis sativus and C. hardwickii during the years 2017 and 2018 using 12 isolates of P. cubensis representing different agroclimatic zones of India. The accession, IC331627 from Dehradun, Uttarakhand showed plant disease index (PDI) ranging from 5.55-20.35 per cent with an average PDI of 11.56 and 11.87 per cent during the years, 2017 and 2018, respectively. Hence, IC331627 was identified to be resistant against the five isolates of P. cubesis (Pc12, Pc17, Pc19, Pc21 and Pc24) and moderately resistant against one isolate (Pc22). This resistant accession C. hardwickii (IC331627) could be utilized to develop mapping population to map genomic regions conferring the resistance to downy mildew in cucumber.","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43850856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Krishna, Priyanka Upadhayay, V. K. Mishra, S. Kujur, Monu Kumar, P. Yadav, Parvin Mahto, Prashant Singh, Ashutosh, Sandeep Sharma, R. Chand
Terminal heat tolerance of 34 wheat genotypes were analyzed for two years. Among 14 traits, canopy temperature, plot yield and days to heading were major components in clustering of genotypes. Three genotypes viz., DBW39, DBW16 and DBW14 had lowest HSI (0.34-0.36) for plot yield and were considered as heat tolerant genotypes by, both, HCA (Hierarchical Cluster Analysis) as well as DA (Discriminant Analysis). These genotypes may serve as potential donors in wheat breeding to improve the terminal heat tolerance.
{"title":"Evaluation of bread wheat (Triticum aestivum L.) for terminal heat tolerance","authors":"S. Krishna, Priyanka Upadhayay, V. K. Mishra, S. Kujur, Monu Kumar, P. Yadav, Parvin Mahto, Prashant Singh, Ashutosh, Sandeep Sharma, R. Chand","doi":"10.31742/ijgpb.80.4.13","DOIUrl":"https://doi.org/10.31742/ijgpb.80.4.13","url":null,"abstract":"Terminal heat tolerance of 34 wheat genotypes were analyzed for two years. Among 14 traits, canopy temperature, plot yield and days to heading were major components in clustering of genotypes. Three genotypes viz., DBW39, DBW16 and DBW14 had lowest HSI (0.34-0.36) for plot yield and were considered as heat tolerant genotypes by, both, HCA (Hierarchical Cluster Analysis) as well as DA (Discriminant Analysis). These genotypes may serve as potential donors in wheat breeding to improve the terminal heat tolerance.","PeriodicalId":13321,"journal":{"name":"Indian Journal of Genetics and Plant Breeding","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43686990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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