Pinot noir crop estimation method allows growers to estimate yields earlier than lag phase

Abstract

Goals: Winegrape growers must estimate yields to prepare for harvest operations and winery processing. Standard practice requires waiting until the lag phase of berry development, which is late for making decisions related to crop thinning, fruit sales, winery inventory, and ordering wine production supplies. Because producers desire improved methods for accurate crop estimation, we evaluated the following questions over six growing seasons for Oregon Vitis vinifera Pinot noir: 1) When does lag phase occur? 2) What cluster weight increase factor should be used with lag phase crop estimation? and 3) Can crop estimation be conducted earlier in the growing season?

Key Findings:

  • The Pinot noir berry development curve was consistent across six years when based on days post-full bloom (50% capfall).
  • The mid-point of lag phase, the most common time to estimate crop yields, was at 55 days post 50% capfall. Lag phase duration was 12 days. Mean cluster weight increase factor during the entire lag phase over the six-year period was 2.1.
  • Cluster weight increase factor equations were developed based on post-budbreak and bloom thermal times and day counts to allow growers flexibility in timing of crop estimation.

Impact and Significance: Data was used to improve upon manual lag phase crop estimation protocols commonly used by winegrape producers, including methods to identify berry lag phase occurrence and developing equations for cluster weight increase factors based on berry development. These modifications may improve the accuracy of manual yield estimates and allow growers to obtain yield estimates earlier in the growing season than previously allowed by standard practice. This methodology may be useful in testing increase factors for other grape cultivars.

Publication
Catalyst: Discovery into Practice, 6(1):30-37
Katherine R. McLaughlin
Katherine R. McLaughlin
Assistant Professor of Statistics

My research interests include sampling methods and social network analysis.