A linear model for predicting olive yield using root characteristics

• Published in: Rhizosphere Vol. 29; p. 100859
• Main Authors: Nasiri, Mohammad Reza, Amiri, Ebrahim, Behzadi, Jalal, Shahinrokhsar, Parisa, Mohammadian Roshan, Naser
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-03-2024
• Subjects: Rhizosphere; Root biomass; Root length; Root weight density; Yield prediction model; Root weight density; Rhizosphere; Root biomass; Yield prediction model; Root length
• ISSN: 2452-2198; 2452-2198
• DOI: 10.1016/j.rhisph.2024.100859

Predicting yield is an important objective in agricultural research. We developed a linear regression model to predict the olive fruit yield (FY) for four olive cultivars (Sivillano, Conservolia, Zard and Clonavis) by monitoring soil moisture, response to root growth and its characteristics including root weight density (RWD), root length (RL) and root biomass (RB). Our results show the model predicts fruit yield based on a simple linear function of root characteristics (R2 = 0.85). A principal component analysis provided a meaningful combined factor (the first principal component) that showed a clear discrimination in olive fruit yield among four cultivars. The model could be applied to rapidly evaluate olive fruit yield using the measured values of root characteristics and to support decision making for orchard management.
•Olive fruit yield (FY) has been obtained by two-year field data monitored.•FY was significantly higher in soils with Conservolia cultivar compared to three other cultivars.•The model developed predicts FY based on linear function of root characteristics with well accuracy.•The model indicates that FY increases with root length, root biomass and root weight density.•The regression coefficient for root length had the highest influence on FY.