热带农业科学2025，Vol.45Issue(6)：6-12,7.DOI:10.12008/j.issn.1009-2196.2025.06.002
不同装样器和土壤粒径对砖红壤有机质与全氮近红外光谱模型建立及预测效果的影响
Effects of Different Samplers and Soil Particle Sizes on the Modeling and Prediction of Organic Matter and Total Nitrogen via Near-Infrared Spectroscopy in the Latosol of Hainan Province
摘要
Abstract
To investigate the basic conditions for the application of near-infrared spectroscopy(NIRS)in soil nutrient analy-sis,this study examined the effects of different samples and particle sizes on the modeling and prediction of soil organic matter and total nitrogen via near-infrared spectroscopy(NIRS)via 72 latitudinal samples from Dalu town,Qionghai,Hainan Prov-ince.The results revealed that theR2values of the soil organic matter and total nitrogen models established with different samples(such as test dishes and test bottles)and soil samples with different particle sizes(1.00 mm and 0.25 mm)were all greater than 0.99.The models for soil organic matter and total nitrogen established with test dish data performed better than those with test bottle data did,with most evaluation parameters(such as RDP,RMSEP,and RE)being superior.The results of organic matter modeling for soils with different particle sizes did not differ significantly,but the prediction of total nitrogen was better for soil samples with a particle size of 0.25 mm.In summary,different samples and soil particle sizes had little impact on the modeling of soil organic matter and total nitrogen by NIRS.However,using test dishes and soil samples with a particle size of 0.25 mm provided better prediction results and can be used as the basis for the application of NIRS for rapid nutrient testing of Latosols in Hainan.关键词
砖红壤/近红外光谱/养分速测/装样器/土壤粒径Key words
Latosol/near-infrared spectroscopy/rapid nutrient testing/sampler/soil particle size分类
农业科技引用本文复制引用
黄天明,王昌跃,姚继涛,祖超,赵雅琦,王灿..不同装样器和土壤粒径对砖红壤有机质与全氮近红外光谱模型建立及预测效果的影响[J].热带农业科学,2025,45(6):6-12,7.基金项目
海南省自然科学基金项目(No.421MS094) （No.421MS094）
海南省胡椒产业技术体系东部综合试验站(No.HNARS-09-Z07) （No.HNARS-09-Z07）
中国热带农业科学院国家热带农业科学中心科技创新团队(No.CATASCXTD202303). （No.CATASCXTD202303）
