A fruit growth approach to estimate oil content in olives

Abstract

Harvest timing in olive orchards has a strong effect on the quality and quantity of oil yield, but many farmers still lack simple and affordable quantitative tools for rationally deciding appropriate harvest dates. This study presents and tests a conceptual model for predicting fruit oil content (Of, g oil fruit−1) from inexpensive measurements of fruit dry weight (wf). The model presents two physiologically relevant parameters, the fruit dry weight at the onset of the oil accumulation phase (wf0) and the ratio of accumulated oil per unit of fruit dry weight increase during the oil accumulation period (β), the latter assumed invariable throughout ripening. A compilation of data on wf and Of dynamics collected from four experiments including six olive cultivars and contrasting conditions of water supply and crop load was used to test the model. Our results suggest that β could be fairly independent of crop load or watering regime and, probably, genetically controlled. By contrast, wf0 is clearly affected by both the cultivar and the availability of assimilates for fruit growth preceding oil accumulation, which makes it orchard- and year-specific. According to those premises, once cultivar-specific β values are available wf0 could be easily calibrated by either a single determination of Of and wf at any time during the oil accumulation phase (Approach A) or by directly measuring wf0 if the date for the onset of oil accumulation can be estimated (Approach B). Validation tests with an independently calibrated β showed an excellent performance for reproducing Of patterns from wf data using Approach A. Approach B satisfactory predicted oil accumulation rates, but absolute estimates of Of were less reliable. Regardless of the calibration approach, the model is easy to implement and has a minimal cost, which satisfies the demand for inexpensive tools for monitoring oil accumulation dynamics.