Environmental characterization and yield gap analysis to tackle genotype-by-environment-by-management interactions and map region-specific agronomic and breeding targets in groundnut

Hajjarpoor, A and Kholová, J and Pasupuleti, J and Soltani, A and Burridge, J and Degala, S B and Gattu, S and Murali, T V and Garin, V and Radhakrishnan, T and Vadez, V (2021) Environmental characterization and yield gap analysis to tackle genotype-by-environment-by-management interactions and map region-specific agronomic and breeding targets in groundnut. Field Crops Research (TSI), 267. pp. 1-15. ISSN 0378-4290

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The high degree of Genotype by Environment by Management (GxExM) interactions is a serious challenge for production and crop improvement efforts. This challenge is especially true for a crop like groundnut that is often grown as a rainfed crop in diverse environments and management, leading to considerable production fluctuations among regions and seasons. Developing a means to characterize the drivers of variable yield and to identify region specific breeding objectives were the main motivations for this research, using groundnut production in India, as a case study for rainfed crops. Historically, five groundnut production areas have been considered by Indian crop improvement programs. Our objectives were to assess the relevance of this zonation system and possibly to re-define production areas with a higher degree of similarities into homogeneous production units (HPUs). Towards this, we used yield gap analysis and the geo-biophysical characters of the production region to understand and deal with GxExM interactions. Weather and soil data, crop parameters, and management information data were collected and groundnut production was simulated at the district scale over 30 consecutive years. Consequently, the geographic distribution of the potential yields and the yield gaps were first estimated to understand the main production limitations in a given region. Large and variable yield gaps (with a mean of ~70 %) were observed and results revealed a readily exploitable production gap (~ 8 M tons), which might be bridged by following recommended agronomic practices. Water deficit limited the yield potential by an average of 40 %, although with large variability among districts. However, large and variable yield gaps remained. To resolve the unexplained variation, principal component and cluster analysis of agronomic model output together with geo-biophysical indicators for each district were carried out. This resulted in seven HPUs, having well-defined production-limiting constraints. Grouping by HPU greatly reduced variance in actual and simulated yields, as compared to grouping across all groundnut production zones in India. The HPU based approach delimited precise geographic regions within which HPU-specific GxM products could be designed by crop improvement programs to boost productivity.

Item Type: Article
Divisions: Research Program : Asia
CRP: CGIAR Research Program on Grain Legumes and Dryland Cereals (GLDC)
Uncontrolled Keywords: Homogeneous production units, Potential yield, SSM model Crop design, Target population of environment
Subjects: Others > Plant Breeding
Mandate crops > Groundnut
Depositing User: Mr Arun S
Date Deposited: 25 Aug 2021 05:19
Last Modified: 25 Aug 2021 05:19
URI: http://oar.icrisat.org/id/eprint/11881
Official URL: https://doi.org/10.1016/j.fcr.2021.108160
Acknowledgement: The authors acknowledge the feedback provided by the groundnut researchers on the HPUs at the expert consultations held during Groundnut Network Group-Asia (GNG-A) meeting at ICRISAT during 26-27 September 2019. The data generated under a project supported by Department of Agriculture, Cooperation and Farmer Welfare of Govt. of India (DAC&FW, GOI) was used for the yield gap analysis and authors acknowledge the data shared by the project collaborators, KL Dobariya (JAU), R Vashathi (ANGRAU, SK Bera (ICAR-DGR) and N Manivannan (TNAU). The senior author was in part supported by a grant the Make Our Planet Great Again (MOPGA) ICARUS project (Improve Crops in Arid Regions and Future Climates) funded by the Agence Nationale de la Recherche (ANR, grant ANR-17-MPGA-0011). We are also grateful to MK Gumma and IA Mohammed for providing the satellite imagery data and Soumyashree Kar for helping in data analysis. The financial assistance to conduct the study in part was received from OPEC Fund of International Development (OFID). The study is conducted under CRPGrain Legumes and Dryland Cereals.
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