Temporal Dependency of Yield and Quality Estimation through Spectral Vegetation Indices in Pear Orchards

Remote Sensing

Jonathan Van Beek⁴  Laurent Tits⁴  Ben Somers⁵  Tom Deckers³  Wim Verjans³  Dany Bylemans⁴  Pieter Janssens¹  Pol Coppin⁴  Tao Cheng²  Clement Atzberger² 

[1] Soil Service of Belgium, Willem de Croylaan 48, BE-3001 Leuven, Belgium; E-Mail:KU Leuven, Department of Biosystems, Division of Crop Biotechnics, Willem de Croylaan 34, BE-3001 Leuven, Belgium;;Pcfruit research station, Fruittuinweg 1, BE-3800 Sint-Truiden, Belgium; E-Mails:;KU Leuven, Department of Biosystems, Division of Crop Biotechnics, Willem de Croylaan 34, BE-3001 Leuven, Belgium; E-Mails:;KU Leuven, Department of Earth and Environmental Sciences, Division of Forest, Nature and Landscape Research, Celestijnenlaan 200E, BE-3001 Leuven, Belgium; E-Mail:

关键词: temporal dependence;    fruit yield and quality estimation;    pyrus communis “conference”;    hyperspectral remote sensing;   

DOI  :  10.3390/rs70809886

来源: mdpi

【 摘 要 】

Yield and quality estimations provide vital information to fruit growers, yet require accurate monitoring throughout the growing season. To this end, the temporal dependency of fruit yield and quality estimations through spectral vegetation indices was investigated in irrigated and rainfed pear orchards. Both orchards were monitored throughout three consecutive growing seasons, including spectral measurements (i.e., hyperspectral canopy reflectance measurements) as well as yield determination (i.e., total yield and number of fruits per tree) and quality assessment (i.e., fruit firmness, total soluble solids and fruit color). The results illustrated a clear association between spectral vegetation indices and both fruit yield and fruit quality (|r| > 0.75; p < 0.001). However, the correlations between vegetation indices and production variables varied throughout the growing season, depending on the phenological stage of fruit development. In the irrigated orchard, index values showed a strong association with production variables near time of harvest (|r| > 0.6; p < 0.001), while in the rainfed orchard, index values acquired during vegetative growth periods presented stronger correlations with fruit parameters (|r| > 0.6; p < 0.001). The improved planning of remote sensing missions during (rainfed orchards) and after (irrigated orchards) vegetative growth periods could enable growers to more accurately predict production outcomes and improve the production process.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.