Integration of Sensor-Based Technology for Modernizing Groundnut Breeding and Enhancing Genetic Gain

Integrating sensor-based technology has significantly transformed groundnut breeding by enhancing precision, improving trait selection, and accelerating genetic gain. This modernization addresses key challenges in phenotyping efficiency, environmental adaptation, and postharvest assessment, ultimately improving breeding outcomes. A key component in this transformation is the Target Population of Environments (TPE) characterization. Breeders can better define representative trial locations and map field variability by combining environmental data with UAV imagery. UAVs equipped with RGB, and multispectral sensors efficiently capture canopy cover, plant height, and biomass across large areas, improving trial design and ensuring selections align with real-world conditions. High-throughput phenotyping platforms like LeasyScan have enhanced the evaluation of critical traits such as early vigor, canopy establishment, and water use efficiency. UAV imaging further strengthens this process by enabling non-invasive, rapid data collection, improving the accuracy of trait selection while reducing labor and evaluation timelines. This improved efficiency is crucial for accelerating genetic gain. Postharvest assessment has also advanced with the adoption of Harvestmaster to correct yields based on moisture content at harvest time. Computed Tomography (CT) imaging offers a non-destructive method for evaluating shelling percentage, kernel weight, and grade. The CT-based pipeline streamlines the assessment process, ensuring superior product quality and enhancing operational efficiency. Nutritional profiling has improved by adopting Near- Infrared Spectroscopy (NIRS), which enables rapid fatty acid profiling. This innovation facilitates the identification of high-oleic acid groundnut lines, supporting breeding programs in developing varieties that meet nutritional and market demands. The groundnut breeding program has improved trait precision, reduced evaluation timelines, and strengthened data quality by integrating UAV imaging, CT imaging, and sensor-based phenotyping tools. These advancements enable better-informed breeding decisions, enhance selection intensity, and shorten breeding cycles, driving genetic gain. The integration of these technologies has positioned ICRISAT’s groundnut breeding program as a model of innovation, ensuring climateresilient development. These high-quality varieties address farmer needs and contribute to sustainable agriculture.

Publication Details

Journal
Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics)
Published
2025-03-01
Primary Topic
Peanut Plant Research Studies
Type
article
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article

Integration of Sensor-Based Technology for Modernizing Groundnut Breeding and Enhancing Genetic Gain

Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics)
Peanut Plant Research Studies
article

Integration of Sensor-Based Technology for Modernizing Groundnut Breeding and Enhancing Genetic Gain

article en

Abstract

Integrating sensor-based technology has significantly transformed groundnut breeding by enhancing precision, improving trait selection, and accelerating genetic gain. This modernization addresses key challenges in phenotyping efficiency, environmental adaptation, and postharvest assessment, ultimately improving breeding outcomes. A key component in this transformation is the Target Population of Environments (TPE) characterization. Breeders can better define representative trial locations and map field variability by combining environmental data with UAV imagery. UAVs equipped with RGB, and multispectral sensors efficiently capture canopy cover, plant height, and biomass across large areas, improving trial design and ensuring selections align with real-world conditions. High-throughput phenotyping platforms like LeasyScan have enhanced the evaluation of critical traits such as early vigor, canopy establishment, and water use efficiency. UAV imaging further strengthens this process by enabling non-invasive, rapid data collection, improving the accuracy of trait selection while reducing labor and evaluation timelines. This improved efficiency is crucial for accelerating genetic gain. Postharvest assessment has also advanced with the adoption of Harvestmaster to correct yields based on moisture content at harvest time. Computed Tomography (CT) imaging offers a non-destructive method for evaluating shelling percentage, kernel weight, and grade. The CT-based pipeline streamlines the assessment process, ensuring superior product quality and enhancing operational efficiency. Nutritional profiling has improved by adopting Near- Infrared Spectroscopy (NIRS), which enables rapid fatty acid profiling. This innovation facilitates the identification of high-oleic acid groundnut lines, supporting breeding programs in developing varieties that meet nutritional and market demands. The groundnut breeding program has improved trait precision, reduced evaluation timelines, and strengthened data quality by integrating UAV imaging, CT imaging, and sensor-based phenotyping tools. These advancements enable better-informed breeding decisions, enhance selection intensity, and shorten breeding cycles, driving genetic gain. The integration of these technologies has positioned ICRISAT’s groundnut breeding program as a model of innovation, ensuring climateresilient development. These high-quality varieties address farmer needs and contribute to sustainable agriculture.

Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics)
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Openalex Percentile: Top 35%
Peanut Plant Research Studies
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