Variety-specific responses to climatic and edaphic factors in cassava productivity - Phanthanong, Phongnapha; Promnikorn, Kanokporn; Kongsil, Pasajee; Kraichak, Ekaphan; Jenweerawat, Sujin; Vuttipongchaikij, Supachai; Kittipadakul, Piya (Frontiers in Agronomy, 2025)
Despite cassava’s significance as a staple crop in tropical and subtropical regions, there is limited understanding of how specific environmental factors influence the productivity of different cassava varieties. This study investigated the complex relationship between environmental factors and cassava yield traits such as fresh root yield (FRY), dry root yield (DRY), starch content (SC) and harvest index (HI) using data obtained from six cassava varieties cultivated for five seasons (2014 to 2019) across nine major locations in Thailand. A total of 41 distinct environmental trials were conducted, representing a range of conditions encompassing various rainfall and temperature patterns, as well as soil characteristics. Field experiments were conducted using a randomized complete block design with four replicates at each location. Climatic data, including air temperature and precipitation, along with soil parameters, were recorded and analyzed to assess their impact on cassava yield traits. Regression analysis revealed distinct coefficients for environmental factors affecting different yield parameters. Cumulative precipitation during 4-5 months after planting (MAP) and 6-10 MAP, as well as the average air temperature during 2-3 MAP and 6-10 MAP, positively influenced cassava yield. However, negative correlations were observed between soil organic matter and HI. Furthermore, the average air temperature at 4-5 MAP, 6-10 MAP, and 1-10 MAP negatively impacts FRY and DRY, while cumulative precipitation during 1 MAP and 2-3 MAP negatively impacts the HI and SC traits. Varieties exhibited varied responses to environmental factors, emphasizing the need to consider specific variety responses for accurate interpretation. The study introduces a novel approach for selecting specific cassava genotypes adapted to distinct environmental conditions by grouping regression coefficients across evaluated parameters. These findings provide insights for optimizing agricultural practices to enhance cassava productivity and contribute to sustainable crop cultivation.