Evaluation under commercial conditions of a model of prediction of the yield and quality of cucumber fruits

Abstract

A mechanistic model was developed to predict the weekly fresh weight yield of cucumber fruits and the fresh weight and developmental stage of the individual fruits at harvest. The latter two being major criteria of fruit quality. The model consists of modules for greenhouse light transmission, light interception by the crop, leaf and canopy photosynthesis, assimilate partitioning, dry matter production, fruit growth, fruit dry matter content and fruit harvest. A sensitivity analysis showed the total yield to increase with increasing radiation, CO 2 concentration and temperature. The harvest strategy of the grower (frequency of harvesting and threshold weight for harvest) had a great impact on simulated fruit size and fruit developmental stage at harvest. The latter was lowest in summer time, which may have consequences for the shelf life of the fruits. The model was validated by comparing simulation results with production data of 10 commercial growers in 1996 and 14 growers in 1997 (January–May). Input data used for validation were week numbers of planting and removing the crop, weekly data on global radiation outside the glasshouse and glasshouse air temperature and daytime CO 2 concentration. The weekly harvest of total fresh weight averaged over all growers was simulated well by the model. The average error of the weekly prediction of the fresh weight yield was 12.6%, while the error of the annual yield was only 0.3% in 1996. The simulated average fruit size corresponded reasonably well with growers' data, showing an average weekly error of 6.6%. The accuracy of prediction of cucumber yields largely depends on accuracy of the weather prediction.