This PPT provides a comprehensive overview of crop modelling in fruit crops, emphasizing the use of quantitative mathematical models to describe, analyze, and predict growth, development, and productivity of perennial fruit trees. It introduces crop modelling as a multidisciplinary subject integrating bioclimatology, soil science, botany, agronomy, applied mathematics, and computer science. The presentation highlights the importance of carbon-based productivity models and plant growth simulation, particularly for understanding fruit tree growth, phenology, and yield under varying environmental and management conditions.
The PPT explains how fruit tree models differ from annual crop models due to their perennial nature, multi-year growth, complex plant architecture, carry-over of physiological status, and strong influence of management practices such as pruning, training, crop load regulation, and grafting on rootstocks. Key differences among fruit tree species, including root system size, reproductive abscission, and bioenergetic cost of fruit production, are discussed.
Various types of crop models are described, including morphological models, process-based models, statistical and empirical models, mechanistic models, deterministic and stochastic models, as well as static and dynamic simulation models. Special emphasis is placed on photosynthesis-based models and functional–structural plant models that combine biomass acquisition and biomass partitioning with plant architecture.
The PPT outlines the prerequisites and steps in crop modelling, such as defining system boundaries, identifying state, rate, driving, and auxiliary variables, quantifying relationships, calibration, validation, and sensitivity analysis. Examples of widely used crop models in fruit crops, including SUCROS, WOFOST, STELLA®, DSSAT, APSIM, and SUGAR, are presented to illustrate practical applications.
Applications of crop models are highlighted in areas such as yield forecasting, phenology prediction, water and nutrient use efficiency, precision farming, on-farm decision making, weather-based agro-advisory services, and evaluation of climate change impacts. Case studies demonstrate the use of simulation models in citrus, apple, peach, and other fruit crops. The PPT also discusses limitations of crop models, including data dependency, complexity, and challenges in representing climatic variability.
Finally, the role of national initiatives such as CHAMAN (Coordinated Horticulture Assessment and Management using Geoinformatics) is described, highlighting the use of remote sensing, GIS, and modelling for horticultural assessment and development. The PPT concludes that although crop models are not universal, they are valuable tools for crop growth prediction, yield analysis, and improved management in fruit crop production