An estimate of potential blueberry yield using regression models that relate the number of fruits to the number of flower buds and to climatic variables
An estimate of potential blueberry yield using regression models that relate the number of fruits to the number of flower buds and to climatic variables
Authors
Salvo, Sonia
Muñoz, Carlos
Ávila, Julio
Bustos, Jaime
Ramirez-Valdivia, Martha
Silva, Carolina
Vivallo Pinare, Gabriel
Muñoz, Carlos
Ávila, Julio
Bustos, Jaime
Ramirez-Valdivia, Martha
Silva, Carolina
Vivallo Pinare, Gabriel
Authors
Date
2012-02-04
Datos de publicación:
10.1016/j.scienta.2011.10.020
Keywords
Arándanos - Modelo de regresión lineal múltiple - Producción
Collections
Abstract
The export of fresh blueberries is an important productive activity in Chile, in terms of the labour employed, the number of hectares cultivated and the resulting trade flow with the northern hemisphere. The export of fresh blueberries requires planning based on early estimates of the yield of the orchard. The growers keep plots with plants of more or less the same age and variety; thus, it is possible to estimate the yield of the whole orchard, based on the yield per plant. Two factors must be considered in estimating the yield per plant: the number of fruits and their fresh weight. An early estimate of the number of fruits can be based on the number of flower buds and their viability during flowering and fruit development. The aim of the research was to find a way of estimating plant yields in commercial orchards by proposing models which relate the number of fruits available for harvest to the number of flower buds and to climatic variables. The estimated value incorporates the fruit weight appropriate to the variety cultivated. When the potential yield estimated is compared to the yield reported by the growers, the estimated errors are less than 12% (overestimation) and the performance achieved by yield models is as high as 0.57 and 0.96 for the correlation coefficients. The obtained models can be used by producers to plan their harvests several months in advance, and can be adjusted to the current season. © 2011 Elsevier B.V.