Temperature- and Radiation-Based Models for Predicting Spatial Growth of Purple Nutsedge (Cyperus rotundus)

被引:17
作者
Lati, Ran Nisim [1 ]
Filin, Sagi
Eizenberg, Hanan
机构
[1] Technion Israel Inst Technol, Haifa, Israel
关键词
Temperature; photosynthetically active radiation; effective degree day; prediction model; leaf-cover area; CYNODON-DACTYLON L; PLANT-GROWTH; L PERS; ESCULENTUS; COVER; BERMUDAGRASS; COMPETITION; EMERGENCE; BIOMASS; TUBERS;
D O I
10.1614/WS-D-11-00007.1
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Purple nutsedge is a troublesome C(4) weed, characterized by high photosynthetic efficiency, compared to C(3) weeds. As its dispersal is based on vegetative growth, accurate prediction of its growth could help in arriving at favorable management decisions. This article details the development and validation of predictive models of purple nutsedge spatial growth, based on temperature (thermal model), and temperature and radiation (photothermal model) measurements. Plants were grown in six experiments in the summers of 2008, 2009, and 2010, under different temperature and radiation conditions. Results indicate that under optimal temperatures, radiation becomes the main growth-limiting factor, and is highly related to the final leaf-cover area (R(2) = 0.89). Comparison of the thermal and photothermal models showed that under all conditions, including varied temperature and radiation, the photothermal model performs significantly better, with differences in root-mean-square error values reaching up to 0.073, compared to 0.195 with the thermal model. Validation experiments confirmed the ability of the photothermal model to predict purple nutsedge spatial growth accurately. Nomenclature: Purple nutsedge, Cyperus rotundus L. CYPRO.
引用
收藏
页码:476 / 482
页数:7
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