.png){kind=icon}
返回
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}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
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.
Keyword:
Rhizosphere
Root biomass
Root length
Root weight density
Yield prediction model
期刊
IF:
3.5
论文数:
1.4K
被引数:
3.0K
机构
引用论文
Bayesian inference of root architectural model parameters from synthetic field data从合成现场数据中贝叶斯推断根建筑模型参数.png)
PLANT AND SOIL
OAAI
PLANT AND SOILIF4.1
OAAI分享收藏Effects of Harvesting Time on Fruit Development Process and Oil Content of Selected Iranian and Foreign Olive Cultivars under Subtropical ConditionsPLANTS-BASELOAAI
PLANTS-BASELIF4.1
OAAI分享收藏分享收藏Applying the SIMPLE Crop Model to Assess Soybean (Glicine max. (L.) Merr.) Biomass and Yield in Tropical Climate VariationAGRONOMY-BASEL
OAAI
AGRONOMY-BASELIF3.4
OAAI分享收藏Effects of length and application rate of rice straw mulch on surface runoff and soil loss under laboratory simulated rainfall室内模拟降雨条件下稻草覆盖长度和施肥量对地表径流和土壤流失的影响
PREAI
分享收藏
查看更多内容