K. B. Gaikwad

Genetic improvement trend analysis for end-use quality characteristics among wheat cultivars of North-Western India

To test the perception among consumers in India for declining nutritional quality of wheat, the trends in enduse quality characteristics of popular wheat cultivars of North Western Plain Zone were studied. Fourteen mega varieties released since 1900 were grown in randomized block design over two years. ANOVA revealed no significant differences for nitrogen percentage in grain as well as straw, however, significant differences among the genotypes within breeding period for kernel hardness, sedimentation value and thousand kernel weights was observed. Linear regression equation for thousand kernel weight indicated a poor gain of 0.036g per year. However, the cubical polynomial regression equation significantly improved the association between kernel weight and year of release (R2 = 0.675). Similarly, cubical polynomial equation indicated continuous decline for sedimentation value with indication of some improvement in recent past. The present study therefore, clearly establishes no perceptible loss in nutritional quality. No trend was observed for flour recovery over the years. The study establishes that breeders did not deliberately modify any of the quality traits except grain plumpness and perceived changes are either not true or due to deterioration in production environment over years. GGE biplot analysis grouped HD 2967, HDCSW 16, HD 3086 along with C 591 and identified HDCSW 16 as the most ideal genotype for grain weight.

Consolidating the yield gain by exploiting genotype × management interaction in wheat

An experiment was conducted with 42 differentially adapted genotypes of wheat for two subsequent years (2011–13) to quantify the genotype × management interaction using additive main effect and multiplicative interaction (AMMI) and genotype main effect (G) plus genotype by environment interaction (GGE) methods. The material was evaluated in three different environments namely, permanent bed (zero tillage) with full residue retention (CA), freshly prepared raised bed with no residue (CTRB) and conventionally tilled and seeded condition i.e. flat bed (CTFB). Genotypic differences for the traits having relevance in adaptation were found significant. Environment followed by genotype × management interaction were found to be the major source of variation for yield, biomass, harvest index (HI) and number of tillers. AMMI biplot pooled six environments (3 management systems and 2 years) into three groups and grouping was slightly different from the grouping done by GGE. As per AMMI analysis, discriminating ability of CA even during stressed year was equal to that of CTFB during more productive year. GGE identified permanent raised bed with residue as most representative and discriminating environment. GGE identified HD3115, HD3117, CSW2, CSW16, CSW18, CSW23 and CSW25 with specific adaptation for CA and CSW35, CTRB1813, CTRB1816, CTRB1817 and CTFB4566 for CTRB. The results clearly suggest that selection and evaluations of breeding material under CA lead to identification of genotypes broadly adapted to other management practices but no vice-versa. CA is the most representative and informative environment and identification and release of CA specific variety can further consolidate the yield.

Central Wheat Hs562'-A High Yielding Wheat Variety for Timely Sown Production Conditions of Northern Hill Zone

Dharam Pal1*, Madhu Patial1, KV Prabhu2, J Kumar1,7, Santosh Watpade1, RN Yadav3, Sanjay Kumar2, RK Sharma2, GP Singh2,8, Rajbir Yadav2, Vinod2, Anju M Singh2, SV Sai Prasad4, IS Solanki6,9, M Sivasamy5, JB Sharma2, PK Singh2, Neelu Jain2, Niharika Mallik2, Kiran Gaikwad2, Tapas Ranjan Das6, Vikas5, Jaya Prakash5, JB Singh2, Divya Ambati4, Vaibhav Singh2, AN Mishra4, Shivadhar2 and Ajay Arora2 1ICAR-IARI, Regional Station, Shimla, India 2ICAR-Indian Agricultural Research Institute, New Delhi, India 3ICAR-Indian Agricultural Research Institute, Regional Station, Karnal, India 4ICAR-Indian Agricultural Research Institute, Regional Station, Indore, India 5ICAR-Indian Agricultural Research Institute, Regional Station,Wellington, India 6ICAR-Indian Agricultural Research Institute, Regional Station,Pusa, India 7ICAR-NIBSM, Raipur, India 8ICAR-Indian Institute of Wheat and Barley Research, Karnal, India 9ICAR-Krishi Bhawan, New Delhi

Breeding wheat for yield maximization under conservation agriculture

Wheat based food security is being challenged due to declining profit, deteriorating production environment and changing climatic conditions. Conservation agriculture (CA) imbibing some components of the natural ecosystem can address some of these issues quite effectively. Wheat breeding so far, has managed to increase grain yield mainly by improving harvest index (HI) and adaptation through phenological manipulation. With limited scope for further increase in HI, an increase in biomass appears inevitable for wheat yield consolidation. The conflict between increased biomass and lodging that imposes a limitation to higher grain yield may have an answer in CA. The production environment under CA is much more congenial than conventional and hence offers an opportunity for identification of higher yielding genotypes. The article discusses the breeding issues and key traits for selection for yield maximization under CA. Integrating agronomic perspectives including cropping system, countering the tradeoff between stress adaptation and yield enhancement through management has been proposed. Selection indices build around increased coleoptile length, weed competitiveness, mild vernalization, increased duration and higher biomass could facilitate the development of CA adapted genotypes. These traits can be further fine-tuned according to different cropping and management practices.

Genetic and time series analysis for grain growth rate and grain filling duration under conservation agriculture in wheat (Triticum aestivum L.)

Grain filling rate (GFR) and grain filling duration (GFD) are most important growth traits. Therefore, the present investigation was carried out to analyze the trend for these traits in the mega varieties released at the different time and to identify the type of gene action governing these traits. The study showed continuous improvement in grain filling rate over time and there is no indication of its saturation and therefore, can be further explored to achieve yield gains. Grain filling duration indicates no change in mega varieties over time for normal sown condition largely because of the trade-off between time and heat stress, however, conservation agriculture condition can provide an opportunity for its exploitation. Under late sown linear regression showed a strong declining trend over the years. The analysis of variance revealed the presence of significant genetic variability, not only among the elite breeding material specifically developed for conservation agriculture (CA) condition but also among released varieties, indicating sufficient scope for their exploitation. Diallel analysis of 21 F1s generated from 7 parents for GFD and GFR indicated the preponderance of additive gene action in the material validating the effectiveness of progeny based selection for both traits under study. Elite breeding material CSW02 displayed high GCA for both the traits and therefore, can be effectively involved in the crossing program to make further gain. Cross CSW77 × CSW57 having a high value of SCA effect for both GFR and GFD provide scope for its exploitation through hybrid development.

Exploring indicator scoring as a selection tool in plant breeding: A study under conservation vs conventional tillage systems

Indian agriculture is on an edge of transition from conventional to conservation agriculture, the only limiting constrant is avaliblity of cultivars adapted to conservation agriculture. This study explores possibility of indicator scoring system for identification of genotypes suitable for different tillage management system namely, conventional tillage flat bed (CTFB) and conservation agriculture (CA). Minimum data set (MDS) was constructed by selecting the traits from each of five principal components (PC) accounting for 71.26% of total variation. Multiple linear regression between MDS as independent variable and yield and biomass as dependent variable showed R2 value of 0.661 and 0.605. Indicator score identified through nonlinear scoring of the MDS found out CA as a superior environemt to conventional agriculture in both years. Indicator score identified HD3117 and HDCSW 18 for CA which support the use of indicator scoring as a selection tool in plant breeding as both of these lines are the product of systematic breeding under CA condition and have revealed significant superiority over other in multilocational yield trials for CA.

Deciphering yield formation process in wheat under contrasting tillage conditions

Non-availability of the genotypes bred under conservation agriculture practices and presence of large interaction for genotype x management, points to the fact that the gain can be further consolidated through cultivation of specifically adapted genotypes under conservation agriculture (CA) in India. Differentially adapted 42 genotypes were grown for two consecutive years under three tillage conditions. During favorable year (2011–12) for crop growth, conservation agriculture (CA) provided the opportunity for benefits of traits like seed width, seed length, embryo width, initial vigour indicated by normalized difference vegetation index (NDVI), shoot biomass and days to maturity to be accumulated into higher biomass at harvest and higher grain yield realization due to improved harvest index (HI). Simultaneously, under conventional tillage raised bed condition probably due to poor water retention, traits relevant for moisture stress condition like NDVI 1 representing initial vigour and more ground coverage in vegetative stage, peduncle length, last node length, biomass, HI showed positive correlation with yield. Changing association between traits under different management condition warrants for caution in the selection criterion Path analysis shows that selection for higher biomass with better HI and higher yield under CA can lay foundation for realization of better gain for yield in future.