Growth and yield estimation of banana through mathematical modelling: a systematic review

Abstract Banana is one of the main fruit crops in world as it a rich source nutrients and has recently become popular for its fibre, particularly raw material many industries. Mathematical models are crucial strategic forecasting applications; however, related to banana crop less common, reviews on previous modelling efforts scarce, emphasizing need evidence-based studies this topic. Therefore, we reviewed 75 full-text articles published between 1985 2021 information mathematical growth and, fibre yield. We analysed results order provide descriptive synthesis selected studies. According co-occurrence analysis, most were conducted production. Modellers often used multiple linear regression estimate plant Existing incorporate range predictor variables, conditions, varieties, approaches evaluation methods, which limits comparative selection best model. However, process-based simulation model ‘SIMBA’ artificial neural network have proven their robust applicability growth. This review shows that there insufficient could aid stakeholders identifying strengths limitations existing models, well providing insight how build novel reliable crop-related models.