.png){kind=icon}
Return
A linear model for predicting olive yield using root characteristics
.png){kind=icon}
PRE
AI
DOI：10.1016/j.rhisph.2024.100859.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Rhizosphere
Root biomass
Root length
Root weight density
Yield prediction model
Journal
IF:
3.5
Papers:
1.4K
Citations:
3.0K
Organization
Cited Papers
Bayesian inference of root architectural model parameters from synthetic field data.png)
PLANT AND SOIL
OAAI
PLANT AND SOILIF4.1
OAAIShareSaveShareSaveEffects of Harvesting Time on Fruit Development Process and Oil Content of Selected Iranian and Foreign Olive Cultivars under Subtropical ConditionsPLANTS-BASELOAAI
PLANTS-BASELIF4.1
OAAIShareSaveShareSaveApplying the SIMPLE Crop Model to Assess Soybean (Glicine max. (L.) Merr.) Biomass and Yield in Tropical Climate VariationAGRONOMY-BASEL
OAAI
AGRONOMY-BASELIF3.4
OAAIShareSaveShareSave
View more