Fruit transpiration in kiwifruit: environmental drivers and predictive model

Abstract

In most fruit crops, storage quality varies greatly between regions and seasons, causing significant commercial loss. Understanding the sources of this variability will contribute to the knowledge of fruit developmental physiology and may also benefit commercial fruit production via altered managements that reduce it or forecasts that predict it. A causal-chain relationship is proposed to help elucidate the sources of variability in fruit storage quality: the weather →(i)→ fruit transpiration →(ii)→ fruit calcium →(iii)→ fruit storage quality. This paper explores the first link of this hypothesis, →(i)→, for Hayward kiwifruit using field measurements of fruit transpiration rate and concurrent meteorological recordings. The aims are to identify the key environmental variables driving fruit transpiration and develop a predictive fruit transpiration model. Fruit transpiration was determined hourly over several 24-h periods by recording weight loss of detached fruit, on Days 23, 35, 49, 65, 94 and 140 after full bloom. Meteorological records were made every 15 min throughout the season at an adjacent regional weather station. A model of fruit transpiration was developed in which the usual meteorological variables (radiation, temperature, windspeed and relative humidity) were incorporated in a Fick's Law transpiration flux equation. Fruit transpiration rate (i.e. the molar flux density, mmol cm(-2) h(-1)) varied diurnally and decreased during the season. The dominant fruit variable governing transpiration rate was skin conductance and the dominant environmental variables were relative humidity and temperature. Radiation and windspeed were not significantly influential. The model provides a good fit to the fruit transpiration rate measurements regardless of the time of day/night or the stage of fruit development. The model allows reasonably accurate and continuous predictions of fruit transpiration rate throughout fruit development based on standard meteorological recordings. It also allows estimates of cumulative fruit transpiration throughout the season.