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ARS Home » Southeast Area » Tifton, Georgia » Crop Genetics and Breeding Research » Research » Publications at this Location » Publication #358915

Research Project: Improvement of Genetic Resistance to Multiple Biotic and Abiotic Stresses in Peanut

Location: Crop Genetics and Breeding Research

Title: Climate-smart groundnuts for achieving high productivity and improved quality: current status, challenges and opportunities

Author
item GANGURDE, SUNIL - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item KUMAR, RAKESH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item PANDEY, ARUN - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item BUROW, MARK - Texas A&M Agrilife
item LAZA, HAYDEE - Texas Tech University
item NYAK, SPURTHI - University Of Agricultural Sciences
item Guo, Baozhu
item LIAO, BOSHOU - Chinese Academy Of Agricultural Sciences
item BHAT, RAMESH - University Of Agricultural Sciences
item MADHURI, NAGA - Acharya Ng Ranga Agricultural University (ANGRAU)
item HEMALATHA, S - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item SUDINI, HARI - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item JANILA, PASUPULETI - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item LATHA, PUTTA - Acharya Ng Ranga Agricultural University (ANGRAU)
item KHAN, HASAN - University Of Agricultural Sciences
item MOTAGI, BABU - University Of Agricultural Sciences
item RADHAKRISHNAN, T - Icar-Indian Institute Of Maize Research
item PUPPALA, NAVEEN - New Mexico State University
item VARSHNEY, RAJEEV - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item PANDEY, MANISH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 12/28/2018
Publication Date: 2/16/2019
Citation: Gangurde, S.S., Kumar, R., Pandey, A.K., Burow, M., Laza, H.E., Nyak, S.N., Guo, B., Liao, B., Bhat, R.S., Madhuri, N., Hemalatha, S., Sudini, H.K., Janila, P., Latha, P., Khan, H., Motagi, B.N., Radhakrishnan, T., Puppala, N., Varshney, R.K., Pandey, M.K. 2019. Climate-smart groundnuts for achieving high productivity and improved quality: current status, challenges and opportunities. Book Chapter. p. 133-172. https://doi.org/10.1007/978-3-319-93536-2_3.
DOI: https://doi.org/10.1007/978-3-319-93536-2_3

Interpretive Summary: Agriculture is highly associated with the climate and the resulting consequences, which impact food production across the globe. Global climate change (CC) has become a major issue for the world agriculture and food security. Peanut is one of the most important oilseed and food crops, but also faces a great challenge to abiotic stress such high drought and high temperature and diseases, which results in losses in production and quality. The consequence of climate change has been observed globally, highlighting the pressing need of designing climate-smart (CS) crops which can withstand these unfavorable conditions and enhance sustainable agriculture to achieve food security. Improved crop genetics benefited increased crop production and quality to meet food and nutritional security of the growing population and enabled cultivation of crops under various biotic and abiotic constrains. Use of modern genetics and genomics technologies are likely to help in improved understanding and efficient breeding for climate smart traits such as tolerance to drought and heat stresses and diseases. The novel promising technologies such as molecular-assisted breeding selection and genome-editing need to be tested for their potential utility in developing climate smart peanut varieties. System modeling may further improve the understanding and characterization of the problems of target ecologies for developing strategies to overcome the problem. The combination of conventional breeding with genomics and system modelling approaches will be an era of system biology assisted breeding for sustainable agricultural production to sustain the ever-growing human population.

Technical Abstract: About 90% of total groundnut is cultivated in the semi-arid tropic (SAT) regions of the world as a major oilseed and food crop, and provides essential nutrients required by human diet. Climate change is a main threat to yield and quality of the products in the SAT regions, and effects are also being seen in some temperate areas. Rising CO2 levels, erratic rainfall, humidity, short episodes of high temperature and salinity hampers the physiology, disease resistance, fertility, yield as well as seed nutrient levels of groundnut. To meet growing demands of increasing population against the threats of climate change, it is necessary to develop climate smart varieties with enhanced and stable genetic improvements in response to changing climate. Identifying the traits affected by climate change in groundnut will be key for developing appropriate strategy for developing new varieties. Fast changing scenarios of product ecologies because of climate change needs faster development and replacement of improved varieties in farmers’ fields to sustain the yield and quality. Use of modern genomics technology is likely to help in improved understanding and efficient breeding for climate smart traits such as abiotic stresses (drought and heat tolerance) and biotic stresses (foliar diseases, stem rot, and pre-harvest aflatoxin contamination). The novel promising technologies such as genomic selection and genome-editing need to be tested for their potential utility in developing climate smart groundnut varieties. System modeling may further improve the understanding and characterization of the problems of target ecologies for developing strategies to overcome the problem. The combination of conventional breeding techniques with genomics and system modelling approaches will be an era of system biology assisted breeding for sustainable agricultural production to sustain the ever-growing population.