Mishra J.S.,Directorate of Sorghum Research |
Thakur N.S.,Directorate of Sorghum Research |
Singh P.,MPUAT |
Singh P.,Directorate of Sorghum Research |
And 8 more authors.
Indian Journal of Agronomy
A field experiments was conducted under All India Coordinated Sorghum Improvement Project (AICSIP) at 6 locations during the rainy seasons of 2009 and 2010 in a split-plot design having 3 tillage systems in main plots and 4 nutrient-management practices in subplots with 3 replications, to find out their effects on productivity, profitability and energetics of sorghum [Sorghum bicolor (L.) Moench]. Conventional tillage resulted in higher grain yield (3.12 t/ha), N, P and K uptake, net returns (`23.5 × 103/ha) and output energy (251 × 103 MJ/ha) than reduced and minimum tillage systems. Application of recommended dose of nutrients (80: 40: 40 N: P2O5, K2O kg/ha) through inorganic fertilizers proved significantly superior in terms of grain yield (3.32 t/ha), net returns (26.6 × 103/ha) and output energy (`267 × 103 MJ/ha) over rest of the treatments. © 2014, Indian Society of Agronomy. All rights reserved. Source
Aruna C.,Direct Of Sorghum Research |
Rakshit S.,Direct Of Sorghum Research |
Shrotria P.K.,Govind Ballabh Pant University of Agriculture & Technology |
Pahuja S.K.,CCS Haryana Agricultural University |
And 6 more authors.
Journal of Agricultural Science
Forage sorghum is an important component of the fodder supply chain in the arid and semi-arid regions of the world because of its high productivity, ability to utilize water efficiently and adaptability to a wide range of climatic conditions. Identification of high-yielding stable genotypes (G) across environments (E) is challenging because of the complex G × E interactions (GEI). In the present study, the performance of 16 forage sorghum genotypes over seven locations across the rainy seasons of 2010 and 2011 was investigated using GGE biplot analysis. Analysis of variance revealed the existence of significant GEI for fodder yield and all eight associated phenotypic traits. Location accounted for a higher proportion of the variation (0·72-0·91), while genotype contributed only 0·06-0·21 of total variation in different traits. Genotype-by-location interactions contributed 0·02-0·13 of total variation. Promising genotypes for fodder yield and each of the associated traits could be identified effectively using a graphical biplot approach. The majority of test locations were highly correlated. A 'Which-won-where' study partitioned the test locations into two mega-environments (MEs): ME1 was represented by five locations with COFS 29 as the best genotype, while ME2 had two locations with S 541 as the best genotype. The existence of two MEs suggested a need for location-specific breeding. Genotype-by-trait biplots indicated that improvement for forage yield could be achieved through indirect selection for plant height, leaf number and early vigour. Copyright © Cambridge University Press 2015. Source
Agricultural Engineering International: CIGR Journal
Grading of agricultural produce especially the fruits and vegetables has become a perquisite of trading across borders. In India mostly fruit growers grade the fruit manually. Manual grading was carried out by trained operators who considered a number of grading factors and fruit were separated according to their physical quality. Manually grading was costly and grading operation was affected due to shortage of labor in peak seasons. Human operations may be inconsistent, less efficient and time consuming. New trends in marketing as specified by World Trade Organization (WTO) demand high quality graded products. Farmers are looking forward to having an appropriate agricultural produce-grading machine in order to alleviate the labor shortage, save time and improve graded product's quality. Grading of fruits is a very important operation as it fetches high price to the grower and improves packaging, handling and brings an overall improvement in marketing system. The fruits are generally graded on basis of size and graded fruits are more welcome in export market. Grading could reduce handling losses during transportation. Grading based on size consists of divergent roller type principle having inclination, expanding pitch type, inclined vibrating plate and counter rotating roller having inclination type graders. Weight grading based on density and specific gravity of agricultural commodities. The need to be responsive to market demand places a greater emphasis on quality assessment, resulting in the greater need for improved and more accurate grading and sorting practices. Size variation in vegetables like potatoes, onions provided a base for grading them in different categories. Every vegetable producing country had made their own standards of different grades keeping in view the market requirements. Source
Aruna C.,DSR |
Bhagwat V.R.,DSR |
Sharma V.,MPUAT |
Hussain T.,MPUAT |
And 4 more authors.
Sorghum shoot fly (Atherigona soccata) is a serious pest that destabilizes the performance of sorghum cultivars and ultimately reduces sorghum production in many parts of the world. Identifying sorghum genotypes with stable resistance to shoot fly is important as it helps to reduce the cost of cultivation and stabilizes yields. In the present study, our objective was to identify stable shoot fly resistant genotypes among 385 recombinant inbred lines (RILs) of a cross between a susceptible parent and a resistant parent. We evaluated this set of RILs in eight environments over three years (2006-2008) for shoot fly resistance and component traits. Non-significant genotype-environment (G × E) linear component and significant pooled deviation for deadheart percentage indicated that the performance of genotypes was unpredictable over the environments. However, five lines had deadheart percentages much less than the population mean with regression coefficient (bi) values close to unity, and non-significant deviation from regression, indicating that they have stable shoot fly resistance and are well adapted to all the environments. Additive main effect and multiplicative interaction (AMMI) analysis partitioned main effects into genotype, environment and G × E interacts with all the components showing highly significant effects (p < 0.001). Environment had the greatest effect (69.2%) followed by G × E interactions (24.6%) and genotype (6.2%). Low heritability and high environmental influence for deadheart percentage suggested that shoot fly resistance is a highly complex character, emphasizing the need for marker assisted selection. We observed transgressive variation in the RIL population for all the traits indicating the contribution of alleles for resistance from both resistant and susceptible parents. Since the alleles for shoot fly resistance are contributed by both resistant and susceptible parents, efforts should be made to capture favourable alleles from resistant and susceptible genotypes. © 2011 Elsevier Ltd. Source
Aruna C.,Directorate of Sorghum Research |
Bhagwat V.R.,Directorate of Sorghum Research |
Madhusudhana R.,Directorate of Sorghum Research |
Sharma V.,MPUAT |
And 5 more authors.
Theoretical and Applied Genetics
Shoot fly is one of the most important pests affecting the sorghum production. The identification of quantitative trait loci (QTL) affecting shoot fly resistance enables to understand the underlying genetic mechanisms and genetic basis of complex interactions among the component traits. The aim of the present study was to detect QTL for shoot fly resistance and the associated traits using a population of 210 RILs of the cross 27B (susceptible) × IS2122 (resistant). RIL population was phenotyped in eight environments for shoot fly resistance (deadheart percentage), and in three environments for the component traits, such as glossiness, seedling vigor and trichome density. Linkage map was constructed with 149 marker loci comprising 127 genomic-microsatellite, 21 genic-microsatellite and one morphological marker. QTL analysis was performed by using MQM approach. 25 QTL (five each for leaf glossiness and seedling vigor, 10 for deadhearts, two for adaxial trichome density and three for abaxial trichome density) were detected in individual and across environments. The LOD and R2 (%) values of QTL ranged from 2.44 to 24.1 and 4.3 to 44.1%, respectively. For most of the QTLs, the resistant parent, IS2122 contributed alleles for resistance; while at two QTL regions, the susceptible parent 27B also contributed for resistance traits. Three genomic regions affected multiple traits, suggesting the phenomenon of pleiotrophy or tight linkage. Stable QTL were identified for the traits across different environments, and genetic backgrounds by comparing the QTL in the study with previously reported QTL in sorghum. For majority of the QTLs, possible candidate genes were identified. The QTLs identified will enable marker assisted breeding for shoot fly resistance in sorghum. © 2011 Springer-Verlag. Source