| 2 | High-Throughput Phenotyping:A Platform to Accelerate Crop Improvement显示文摘Development of high-throughput phenotyping technologies has progressed considerably in the last 10 years.These technologies provide precise measurements of desired traits among thousands of field-grown plants under diversified environments;this is a critical step towards selection of better performing lines as to yield,disease resistance,and stress tolerance to accelerate crop improvement programs.High-throughput phenotyping techniques and platforms help unrave-ling the genetic basis of complex traits associated with plant growth and development and targeted traits.This review focuses on the advancements in technologies involved in high-throughput,field-based,aerial,and unmanned platforms.Development of user-friendly data management tools and softwares to better understand phenotyping will increase the use of field-based high-throughput techniques,which have potential to revolutionize breeding strategies and meet the future needs of stakeholders. | Sumit Jangra Vrantika Chaudhary Ram C.Yadav Neelam R.Yadav | 2021 | Phenomics2021，1，2： | 0 |
| 3 | Genetic linkage mapping and QTL identification for salinity tolerance in Indian mustard(Brassica juncea L.Czern and Coss.)using SSR markers显示文摘Soil salinity is one of the major environmental constraints that limits crop yield and nearly 7%of the total area worldwide is affected by salinity.Salinity-induced oxidative stress causes membrane damage during germination and seedling growth.Indian mustard is a major oilseed crop in India and its production and productivity are severely affected by salt stress.Breeding Brassica cultivars for salinity tolerance by conventional means is very difficult and time-consuming.Therefore,understanding the molecular components associated with salt tolerance is needed to facilitate breeding for salt tolerance in Brassica.In this investigation,quantitative trait loci(QTLs)associated with salt tolerance were identified using F_(2:3)mapping population developed from a cross between CS52(salinity tolerant)and RH30(salinity sensitive).Parents and F_(2:3)were evaluated under controlled and salinity stress conditions for 14 morpho-physiological traits for two consecutive generations(F2 and F_(2:3)),explaining proportion of the phenotypic variance under control condition.Simple sequence repeat(SSR)markers were used for mapping studies.A genetic linkage map based on 42 simple sequence repeats(SSRs)markers was constructed covering 2298.5 cM(Haldane)to identify the loci associated with salt tolerance in Brassica juncea.Forty-one SSRs showing polymorphism in the parents(CS52 and RH30)were mapped on 8 linkage groups(C1–C8).One marker(nga 129)did not map to any of the linkage group and was excluded from mapping.Linkage group 5(C5;317.9 cM)was longest and linkage group 1(C1,255.0 cM)was shortest.Further,we identified 15 QTLs controlling 8 traits using F_(2:3)population.These QTLs explained 12.44–60.63%of the phenotypic variation with a LOD score range of 3.62–5.97.Out of these QTLs,QMI4.1 related to membrane injury showed 51.28%phenotypic variance with a LOD score of 3.34.QTL QBYP8.1 related to biological yield per plant showed 60.63%phenotypic variance at a LOD score of 3.62.The highest LOD score of 5.97 was recorded for QTL related to seed yield per plant(QSYP4.1).Major QTLs were QTL for biological yield per plant(QBYP8.1),QTL for siliquae per plant(QSP4.1),QTL for primary branches(QPB4.1),QTLs for seed per siliqua(QSS4.1,QSS4.2),QTL for seed yield per plant(QSYP4.1),and QTL for membrane injury(QMI8.1)which showed more than 50%phenotypic variance.These QTLs identified in our study need to be confirmed in other populations as well so that these can be used in marker-assisted selection and breeding to enhance salt tolerance in Brassica juncea. | Rekha Patel Sumit Jangra Ram Avtar Neelam R.Yadav Ram C.Yadav | 2023 | Oil Crop Science2023，8，3： | 0 |
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