Practical Use of the "MaluSim" Carbon Balance Model to Predict Chemical Thinner Response of Apple

Chemical thinning remains one of the more unpredictable parts of apple production with large variations within years and from year to year. Many factors affect apple thinning response including chemical dose, chemical uptake and fruitlet sensitivity to chemical induced abscission. We have measured this variability each year from 2000-2010 on mature ‘Royal Gala’/M.9, ‘McIntosh’/M.9 and ‘Ace Delicous’/M.26 trees. Our data indicate that the sensitivity of the fruitlets to chemical induced abscission is related both to stage of fruit development and carbohydrate availability to support fruit growth. The variability related to stage of fruit development is evidenced by low sensitivity to chemical thinners of small slow growing fruitlets at petal fall which are usually about 4mm diameter and high sensitivity to rapidly growing fruitlets between 10-15mm. After fruits reach 20mm, they are much less sensitive to chemical thinners even though growth rate is high.  The physiological or genetic basis for the differing sensitivity to chemicals at differing fruitlet stages is not clear.  A second source of variability, is the availability of carbohydrates to support fruit development which we have estimated using a MaluSim carbohydrate prediction model. Model simulations from several years showed that there are often periods of particularly negative or positive carbon supply:demand balance which were associated with severe thinning or mild thinning. Comparisons of carbohydrate availability and thinning also indicate that carbohydrate balance interacts with stage of fruit development resulting in different thinning efficacies due to both carbohydrate supply level and fruit development stage. We have generated a family of response curves which can be used to predict thinning response at various fruit sizes and under different carbohydrate balance conditions.  We have used these curves with the MaluSim model and weather forecasts to predict thinning response for several regions of New York State with good but not perfect success. This information should help growers predict thinning efficacy of sprays and thereby adjust concentrations of chemicals to achieve the optimum crop load.