Golnaz Badr* and Terence Bates
*Cornell University, 6592 W Main Rd, Portland, NY, 14769 (gb482@cornell.edu)

Weather plays a key role in growth and development of Concord (Vitis labruscana Bailey).  Short-term weather variability can lead to variation in annual Concord yield and influence the market. Concord growers need to precisely estimate yield early in the season to make better management decisions such as shoot or fruit thinning. Berry weight is one of the key components for Concord crop estimation. The main objective of this study was to investigate any potential correlation between seasonal weather patterns and berry weight dynamics across multiple growing seasons. Long-term historic weather data were obtained for Lake Erie, NY, and the temperature and precipitation for each growing season was classified into normal, below-normal, or above-normal. Berry weight data were collected on a weekly interval at the Cornell Lake Erie Experimental Vineyard starting 20 days after bloom until harvest for 17 consecutive growing seasons. At harvest, juice soluble solids, pH, titratable acidity, and color of berry samples were also measured. The collected data were then analyzed based on growing season classifications. This classification was later used to estimate berry weight, the results were compared to the observed berry weight, and the bias was computed. In years with a cold and wet July, the average berry weight tended to be higher (3.44 g versus 2.76 g) than in years with a warm and wet July. A strong correlation was found between berry color and maximum temperature (r = 0.7) and rain (r = -0.71) in July. The mean absolute bias averaged 0.24 g and RMSE was 0.25 when the estimated and observed berry weights were compared. This study described the trend between weather variability and berry weight dynamics across multiple growing seasons.

Funding Support: National Institute of Food and Agriculture