LINTUL-Cassava-NPK: A simulation model for nutrient-limited cassava growth

• Published in: Field crops research 2022-05, Vol.281, p.108488-108488, Article 108488
• Main Authors: Adiele, J.G., Schut, A.G.T., Ezui, K.S., Giller, K.E.
• Format: Article
• Language: English
• Subjects: Balanced nutrition; Nutrient equivalents; Nutrient uptake rates; Potassium response; Simulation model
• ISSN: 0378-4290; 1872-6852
• DOI: 10.1016/j.fcr.2022.108488

A solid understanding of the dynamics of plant nutrient requirements and uptake from the soil is needed to provide robust fertilizer recommendations, timing of applications and nutrient use efficiency. Our objective was to develop and test the ability of the crop model LINTUL-Cassava-NPK to simulate biomass growth and yield of cassava under nutrient-limited conditions. We used experimental data from six fields located in three different agro-ecologies in Nigeria: Rainforest Zone– Ogoja and Ikom (Cross River), Rainforest Transition Zone – Ekpoma (Edo) and Guinea Savanna Zone – Otukpo (Benue) over two consecutive growing seasons from 2016 to 2018. Nutrient stress in the model was implemented by combining N, P and K nutrition indices (NI) to account for the interaction of multiple nutrient limitations for crop growth. Nutrient uptake was determined by balancing demand and supply of nutrient equivalents. We parameterized and calibrated the model using observations from an experiment conducted under optimal growing conditions in Edo during the 2016 planting season. The model was then tested with data from experiments conducted in the 2017 season in Edo, Cross River and Benue. The model captured the uptake patterns of N, P and K well. Uptakes of N, P and K, and storage root yield were predicted with a small root mean squared error of 5.1 g N m−2, 0.8 g P m−2, 3.3 g K m−2 and 308 g DM roots m−2, with an R2 of 0.7 – 0.8 for linear relationships between simulated and observed values. The time course of development of nutrient-limited yield of green leaves, stems and storage roots were simulated reasonably well. In general, the model responded aptly to both nutrient omissions and varying amounts of NPK. These findings increase our understanding of nutrient limitations and N, P and K interactions on cassava growth and yield. The model provided insight into surplus amounts of nutrients in the soil at the end of the season and, specifically, the need to balance the supply of N and K for cassava. To our knowledge, this is the first tested cassava process-based model that includes the three macro-nutrients.