Light interception, leaf nitrogen and yield prediction in almonds: A case study
2015
Zarate-Valdez, Jose L. | Muhammad, S. (Saiful) | Saa Silva, S. (Sebastian) | Lampinen, Bruce D. | Brown, P. H. (Patrick H.)
Crop yield prediction is important for the optimization of irrigation water, fertilizers, and other inputs and resources on the farm. In perennial crops, yield prediction is influenced by multiple factors regulated within the tree such as carry over effects from previous years, source-sink interactions and resource allocation and remobilization, but the bases for those regulation mechanisms are not well understood. This study reports the analysis of intensive sampling of light interception, leaf and nut nutrient concentration and yield of 768 almond trees subjected to fertilization and irrigation treatments within a mid-age commercial orchard. Nitrogen fertilization had a significant effect on individual tree fPAR, LAI, leaf nitrogen content and nut yield. While light interception and leaf area index (LAI) were poor predictors of kernel yield (R2=0.16–0.36 for light interception and 0.21–0.40 for LAI), leaf nitrogen pool (LNP) was able to predict 71–76% of the tree yield variability observed in two and three years. Near harvest, the LNP was highly correlated with fruit nitrogen pool (FNP) (R2=0.87). The results indicate that tree yield and nitrogen demand can be predicted based on leaf nitrogen content.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par National Agricultural Library
Découvrez la collection de ce fournisseur de données dans AGRIS