Sampling stratification using aerial imagery to estimate fruit load in peach tree orchards

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Date
2018Author
Version
Acceso abierto / Sarbide irekia
Type
Artículo / Artikulua
Version
Versión publicada / Argitaratu den bertsioa
Impact
|
10.3390/agriculture8060078
Abstract
A quick and accurate sampling method for determining yield in peach orchards could
lead to better crop management decisions, more accurate insurance claim adjustment, and reduced
expenses for the insurance industry. Given that sample size depends exclusively on the variability
of the trees on the orchard, it is necessary to have a quick and objective way of assessing this
variability. The aim ...
[++]
A quick and accurate sampling method for determining yield in peach orchards could
lead to better crop management decisions, more accurate insurance claim adjustment, and reduced
expenses for the insurance industry. Given that sample size depends exclusively on the variability
of the trees on the orchard, it is necessary to have a quick and objective way of assessing this
variability. The aim of this study was to use remote sensing to detect the spatial variability within
peach orchards and classify trees into homogeneous zones that constitute sampling strata to decrease
sample size. Five mature peach orchards with different degrees of spatial variability were used.
A regular grid of trees was established on each orchard, their trunk cross-sectional area (TCSA)
was measured, and yield was measured as number of fruits/tree on the central tree of each one of
them. Red Vegetation Index (RVI) was calculated from aerial images with 0.25 m pixel -1 resolution,
and used, either alone or in combination with TCSA, to delineate sampling strata using cluster fuzzy
k-means. Completely randomized (CRS) and stratified samplings were compared through 10,000
iterations, and the Minimum Sample Size required to obtain estimates of actual production for three
quality levels of sampling was calculated in each case. The images allowed accurate determination
of the number of trees, allowing a proper application of completely randomized sampling designs.
Tree size and the canopy density estimated by means of multispectral indices are complementary
parameters suitable for orchard stratification, decreasing the sample size required to determine fruit
count up to 20–35% compared to completely randomized samples. [--]
Subject
Prunus persica L. Batsch,
Sampling strategy,
Sample size,
Stratification
Publisher
MDPI
Published in
Agriculture 2018, 8, 78
Departament
Universidad Pública de Navarra. Departamento de Agronomía, Biotecnología y Alimentación /
Nafarroako Unibertsitate Publikoa. Agronomia, Bioteknologia eta Elikadura Saila