Improving predictability of time to harvest and yield of field grown tomato crops

Accurate predictions of the timing of harvest and crop yield are of major benefit to large scale commercial tomato growers as they support efficient utilisation of resources and enable planting schedules to be managed so that there is a regular supply of product to the market. The predictive tools available to field tomato growers are limited as most tomato crop models have been developed for greenhouse conditions and indeterminate tomato cultivars. As the success of a crop yield forecasting system strongly depends on the crop simulation models ability to quantify the influence of weather and management practices on plant development, data describing effects of these factors on the key developmental events of flowering and fruit maturity are valuable. In this study the effects of a range of management factors and planting times on flowering and fruit maturation were assessed in field trials and commercial crops. Analysis of commercial crop data from 217 crops grown over three production seasons in the Bundaberg region in Queensland, Australia demonstrated the dominant effect of temperature on crop development and also identified differences in developmental rate due to soil type. Replicated field trials revealed a small but significant effect of crop pruning strategies on flowering time and harvest date. Varying the fruit load on plants pruned to produce different branching patterns induced no significant changes in the photosynthesis rate of the plants, indicating that plasticity in source sink relations exist with new shoots from the axils of the leaves replacing fruit as the major sink in plants with reduced fruit load. It was also observed that varying the branching patterns in field grown tomato had a significant impact on assimilate partitioning and that this response resulted in a significant branching pattern effect on harvesting date of the crops. The fruit maturation rate and first harvesting time of commercial field grown tomato was influenced by pruning strategy, with the optimum strategy being that which maintained a desired source-sink ratio of vegetative and reproductive sink organs for optimum yield of the crops. Base thermal time and seasonal pattern models for prediction of harvest date were developed that provided improved predictability over the current calendar date model used by industry. No adequate prediction of yield was achieved, and much more work is needed in identification of the key factors causing the very large crop to crop differences in yield in commercial production in the study location.