Technology development has progressed in recent decades in terms of breeding and agronomy of major crops such as wheat, rice, and maize. Nevertheless, production of these major crops is under pressure from climate change and threats of marginal soil nutrients in degraded agricultural lands. Underutilized crops are identified as resilient to local environments that can cope with climatic variations. Bambara groundnut, an African legume that is grown in low input subsistence farming systems in sub–Saharan Africa and Asia has been identified as a potential future crop under climate change. Improving its productivity and suitability under future climates and future locations, requires comprehensive analysis of growth and development of Bambara groundnut under different growing conditions. Process-based crop simulation models facilitate the evaluation of management options for variable growing environments and soil conditions. Therefore, the current study was aimed to evaluate growth and development of Bambara groundnut and to adapt the generic legume model CROPGRO for explaining crop response to management and environment. The parameters used for modelling growth and development of peanut () served as the initial reference values for adapting CROPGRO model. Crop information from the published sources were applied to the functions and parameters of the model. Crop phenology, canopy development, growth and yield were calibrated for two contrasting Bambara groundnut landraces using experimental data from controlled-environment experiments conducted in 2003 and 2006 at Tropical Crops Research Unit (TCRU), Sutton Bonington Campus, University of Nottingham, UK. Overall, the model calibration results of Leaf Area Index (LAI), total biomass and yield were well predicted with d-statistics greater than 0.89. The cardinal base temperatures for leaf photosynthesis of Bambara groundnut had to be set higher than those for peanut, in order to simulate the reduced growth observed during relatively low temperatures. The value for the specific leaf weight (SLWREF) at which light-saturated leaf photosynthesis is defined, was increased from 0.0043 to 0.0063 g cm to reduce the productivity of Bambara groundnut compared to peanut. The new model will be incorporated in the DSSAT version 4.8 software and will provide capability for assessing management practices in matching environments and suggesting potential regions for future expansion of Bambara groundnut cultivation into resilient cropping systems.

中文翻译：

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采用 CROPGRO 模型来模拟班巴拉花生 (Vigna subterranea L. Verdc)（一种未充分利用的作物）的生长、发育和产量


近几十年来，小麦、水稻和玉米等主要作物的育种和农艺技术取得了进步。然而，这些主要作物的生产面临着气候变化和退化农田边际土壤养分威胁的压力。未充分利用的作物被认为对当地环境具有适应能力，可以应对气候变化。班巴拉花生是一种非洲豆科植物，在撒哈拉以南非洲和亚洲的低投入自给农业系统中种植，已被确定为气候变化下潜在的未来作物。提高班巴拉花生在未来气候和地点下的生产力和适应性，需要对班巴拉花生在不同生长条件下的生长发育进行综合分析。基于过程的作物模拟模型有助于评估可变生长环境和土壤条件的管理方案。因此，本研究旨在评估班巴拉花生的生长和发育，并采用通用豆类模型 CROPGRO 来解释作物对管理和环境的反应。用于模拟花生生长发育的参数（）作为适应 CROPGRO 模型的初始参考值。来自已发布来源的作物信息被应用于模型的函数和参数。使用 2003 年和 2006 年在英国诺丁汉大学萨顿博宁顿校区热带作物研究中心 (TCRU) 进行的受控环境实验数据，对两种对比鲜明的班巴拉花生地方品种的作物物候、冠层发育、生长和产量进行了校准。 总体而言，叶面积指数（LAI）、总生物量和产量的模型校准结果得到了很好的预测，d统计量大于0.89。班巴拉花生叶片光合作用的基本基础温度必须设置得高于花生，以模拟在相对较低温度下观察到的生长减少。与花生相比，定义光饱和叶片光合作用的叶比重 (SLWREF) 值从 0.0043 g cm 增加到 0.0063 g cm，以降低班巴拉花生的生产力。新模型将被纳入 DSSAT 4.8 版软件中，并将提供评估匹配环境中的管理实践的能力，并为班巴拉花生种植未来扩展为弹性种植系统提供潜在区域建议。