Fast And Simultaneous Prediction Of Agricultural Soil Nutrients Content Using Infrared Spectroscopy

D. Devianti, Z. Zulfahrizal, S. Sufardi, A. A. Munawar
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Abstract

Abstract. The functions soil depends on the balances of its structure, nutrients composition as well as other chemical and physical properties. Conventional methods, used to determine nutrients content on agricultural soil were time consuming, complicated sample processing and destructive in nature. Near infrared reflectance spectroscopy (NIRS) has become one of the most promising and used non-destructive methods of analysis in many field areas including in soil science. The main aim of this present study is to apply NIRS in predicting nutrients content of soils in form of total nitrogen (N). Transmittance spectra data were obtained from a total of 18 soil samples from 8 different sites followed by N measurement using standard laboratory method. Principal component regression (PCR) with full cross validation were used to develop and validate N prediction models. The results showed that N content can be predicted very well even with raw spectra data with coefficient correlation (r) and residual predictive deviation index (RPD) were 0.95 and 3.35 respectively. Furthermore, spectra correction clearly enhances and improve prediction accuracy with r = 0.96 and RPD = 3.51. It may conclude that NIRS can be used as fast and simultaneous method in determining nutrient content of agricultural soils.
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红外光谱法快速同时预测农业土壤养分含量
摘要土壤的功能取决于其结构、营养成分以及其他化学和物理性质的平衡。传统的农业土壤养分含量测定方法耗时、样品处理复杂、破坏性强。近红外反射光谱(NIRS)已成为包括土壤科学在内的许多领域中最有前途和最常用的无损分析方法之一。本研究的主要目的是将近红外光谱应用于以总氮(N)形式预测土壤养分含量。从8个不同地点的18个土壤样品中获得了透射光谱数据,然后使用标准实验室方法进行了N测量。采用完全交叉验证的主成分回归(PCR)来开发和验证N预测模型。结果表明,即使使用原始光谱数据,氮含量也可以很好地预测,系数相关性(r)和残差预测偏差指数(RPD)分别为0.95和3.35。此外,光谱校正明显增强和提高了预测精度,r=0.96,RPD=3.51。结果表明,近红外光谱法是一种快速、同时测定农业土壤养分含量的方法。
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