Plant growth modeling in six landraces of Bambara groundnut seed production (Vigna subterranea)

Abstract. Rosyad A, Ilyas S, Qadir A, Suhartanto MR, Sopandie D. 2025. Plant growth modeling in six landraces of Bambara groundnut seed production (Vigna subterranea). Biodiversitas 26: 2097-2105. The unavailability of high-quality seeds, low productivity, and lack of information on ecophysiological responses are the major problems in Bambara groundnut (Vigna subterranea) seed production. In this context, agro-climate components influencing plant growth include solar radiation and temperature. These components are quantified in the form of a plant model to influence growth through metabolic processes. A dynamic model is used as a solution to the problem. Therefore, this research aimed to create a dynamic model for the seed production of six Bambara groundnut landraces and to study the physiological processes related to yield. The stages in the model construction included (i) identifying system components, (ii) model construction, (iii) simulation, and (iv) validation. The ecophysiological reaction of plants to temperature and solar radiation in photosynthesis and respiration was constructed using the growth model. Model construction used the STELLA software. Each landrace has different input components at each stage of development, including the carbohydrate partition coefficient, specific leaf area, extinction coefficient, and light usage efficiency. Simulated seed productivity on Tasikmalaya, Sukabumi, Sumedang, Small Sumedang, Bogor, and Gresik landrace was 2,115 kg ha-1, 2,263 kg ha-1, 1,975 kg ha-1, 1,890 kg ha-1, 2,179 kg ha-1, and 1,975 kg ha-1, respectively. The level of validity of the Tasikmalaya landrace, Sukabumi, Sumedang, Small Sumedang, Bogor, and Gresik growth model reached 82.4%, 82.4%, 94.1%, 82.4%, 88.2%, and 82.4%, respectively. These models are considered fit as the validity is greater than 80%. The seed production growth model with pod dry weight output was named 'The BAMSeed Model'. In practice, this model could benefit the researchers in predicting the yield of bambara groundnut using the selected system components.