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2017 ASHS Annual Conference

Non-destructive Dry Matter Prediction in d’Anjou Pears: A New Sorting Tool?

Wednesday, September 20, 2017: 11:30 AM
Kohala 2 (Hilton Waikoloa Village)
Sara Serra, Washington State University, Wenatchee, WA
Alex Goke, Washington State University, Wenatchee, WA
Angela Knerl, Washington State University, Wenatchee, WA
Ryan Sheick, Washington State University, Wenatchee, WA
Stefano Musacchi, Washington State University, Wenatchee, WA
Dry matter concentration is currently becoming more and more important in the horticultural sector as it is related to eating quality, maturity, and ultimately to consumer preference. It has been used in kiwifruit to determine the appropriate picking time, and in apples was shown to be a good predictor of total soluble solids after 3 months in storage. In other crops, a higher dry matter at harvest is related to greater consumer acceptability of the product after storage and an increased likelihood to purchase. A ‘d’Anjou’ pear commercial orchard located in WA and grafted on OHF87 in 1998 with a planting density of 957 trees/ha was the object of this study. Four pruning treatments were compared for dry matter accumulation in fruit during the 2016 season: winter pruning (WP), winter+summer pruning (W+SP), fall pruning (FP) and fall+summer pruning (F+SP). Five hundred fruit per treatment were measured by the Felix F-750 Fruit Quality Meter for a non-destructive dry matter % (DM) and SSC (Brix) prediction. All fruit were sorted by DM from the lowest to highest % in to six classes (from 11 to 18% where possible). Fruit were then divided in to two storage periods - T0q (fruit quality analysis at T0, September 2016) and T1q (fruit quality analysis at T1= after five months of storage at 0.5°C, beginning of February 2017). Fruit quality parameters assessed were as follows: skin color parameters (L, a, b), red blush, over-color percentage, weight, IAD index, firmness, soluble solids content (SSC, destructive), exogenous ethylene concentration, cork incidence, % dry matter (destructive), titratable acidity, and pH after seven days of ripening at room temperature. Fruit quality data analyzed by DM classes, regardless of pruning treatment, revealed significant differences among them. Pears in the lowest DM class were found to be smaller by size and weight than all other dry matter classes. Fruits in the lower two DM classes had significantly higher IAD index immediately after storage and the smallest decrease in IAD index in seven days of ripening at room temperature than all other classes, suggesting lower maturity. Lower DM classes tended to have fruits that were more firm and had lower SSC (Brix). The non-destructive assessment of dry matter by Felix F-750 has potential for use as a sorting tool to predict final pear quality and to determine the relationship of different DM pear categories with consumer acceptance.
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