Evaluation of a Preharvest Bioclimatic Model for Predicting the Risk of Low Temperature Disorders of Stored Apples in Canada and France

Bourgeois, G; Plouffe, D.; DeEll, Jennifer R.; Pitiot, C.

doi:10.17660/actahortic.2015.1068.30

Cited by 1 publication

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“…This was actually lower than predictions from the SBI dyn model (67.9%) as well as lower than the SBI reg model (71.4%). Predictions from the LTD-riskV2 model (Bourgeois et al, 2014b) supported that 'Honeycrisp' apples react either to different weather conditions or different weights associated with these weather conditions of temperature and solar radiation, which were highly correlated with the number of days with precipitation.…”

Section: Year Of Harvestmentioning

confidence: 90%

“…Comparisons between predictions from the soggy breakdown model developed in this study and predictions from the LTD-riskV2 model developed at Agriculture and Agri-Food Canada (Bourgeois et al, 2014b) using the same sites and years of harvest and weather stations were also conducted.…”

Section: Postharvest Biology and Technologymentioning

confidence: 99%

“…A model exists for the risk index of lowtemperature disorders (LTD-riskV2), which was mainly built from observations of vascular browning in 'McIntosh' and 'Cortland' apples, developed with weather data from five regions in Quebec from 1977 to 1995, and implemented in the Computer Center for Agricultural Pest Forecasting (CIPRA) software (Bourgeois et al, 2014b). This model mainly uses functions that include maximum and minimum temperatures and solar radiation during the months of July and August.…”

mentioning

confidence: 99%

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Modeling the Effect of Preharvest Weather Conditions on the Incidence of Soggy Breakdown in ‘Honeycrisp’ Apples

Lachapelle¹,

Bourgeois²,

DeEll³

et al. 2017

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‘Honeycrisp’ is a relatively new apple cultivar highly susceptible to physiological disorders, such as soggy breakdown. The overall objective of this study was to identify preharvest weather parameters that influence the incidence of soggy breakdown over the different phases of fruit development. Using weather data and evaluation of fruit quality from three sites in Ontario, two sites in Quebec, and one site in Nova Scotia from 2009 to 2011, and data from four sites in Ontario from 2002 to 2006, a model for soggy breakdown incidence (SBI) was developed to predict the level of susceptibility in ‘Honeycrisp’ apples. This model uses primarily two weather variables during the last phase of fruit development [91 days from full bloom (DFB) to harvest] to accumulate an SBI index during the growing season, from full bloom to harvest. Cool (temperature <5 °C) and wet conditions (precipitation >0.5 mm) during this last phase resulted in increased soggy breakdown susceptibility levels. The predictions of the SBI model resulted in 68% of well-estimated cases (threshold of ±5%) (RMSE = 6.45, EF = 0.28, E = −0.04). Furthermore, firmness was linked to soggy breakdown, in addition to weather conditions, revealing a positive effect of high firmness at harvest on the development of the disorder. However, the effect of fruit quality attributes (e.g., internal ethylene concentration, starch index, firmness, and soluble solid content) by themselves, without considering weather conditions, revealed no relationship with the incidence of soggy breakdown.

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Section: Year Of Harvestmentioning

confidence: 90%

Section: Postharvest Biology and Technologymentioning

confidence: 99%

mentioning

confidence: 99%

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