Fuentes Mariela, González-Martín Inmaculada, Hernández-Hierro Jose Miguel, Hidalgo Claudia, Govaerts Bram, Etchevers Jorge, Sayre Ken D, Dendooven Luc
Colegio de Postgraduados, Laboratorio de Fertilidad, IRENAT Km 36.5 Carretera México-Texcoco, Montecillo, México, CP 56230, Mexico.
Talanta. 2009 Jun 30;79(1):32-7. doi: 10.1016/j.talanta.2009.03.002. Epub 2009 Mar 13.
In the present study the natural abundance of (13)C is quantified in agricultural soils in Mexico which have been submitted to different agronomic practices, zero and conventional tillage, retention of crop residues (with and without) and rotation of crops (wheat and maize) for 17 years, which have influenced the physical, chemical and biological characteristics of the soil. The natural abundance of C13 is quantified by near infrared spectra (NIRS) with a remote reflectance fibre optic probe, applying the probe directly to the soil samples. Discriminate partial least squares analysis of the near infrared spectra allowed to classify soils with and without residues, regardless of the type of tillage or rotation systems used with a prediction rate of 90% in the internal validation and 94% in the external validation. The NIRS calibration model using a modified partial least squares regression allowed to determine the delta(13)C in soils with or without residues, with multiple correlation coefficients 0.81 and standard error prediction 0.5 per thousand in soils with residues and 0.92 and 0.2 per thousand in soils without residues. The ratio performance deviation for the quantification of delta(13)C in soil was 2.5 in soil with residues and 3.8 without residues. This indicated that the model was adequate to determine the delta(13)C of unknown soils in the -16.2 per thousand to -20.4 per thousand range. The development of the NIR calibration permits analytic determinations of the values of delta(13)C in unknown agricultural soils in less time, employing a non-destructive method, by the application of the fibre optic probe of remote reflectance to the soil sample.
在本研究中，对墨西哥农业土壤中（13）C的自然丰度进行了量化，这些土壤采用了不同的农艺措施，包括零耕和传统耕作、保留或不保留作物残茬以及作物（小麦和玉米）轮作，为期17年，这些措施影响了土壤的物理、化学和生物学特性。通过使用远程反射光纤探头的近红外光谱（NIRS）对C13的自然丰度进行量化，将探头直接应用于土壤样品。近红外光谱的判别偏最小二乘分析能够对有残茬和无残茬的土壤进行分类，无论使用何种耕作或轮作系统，内部验证的预测率为90%，外部验证的预测率为94%。使用改进的偏最小二乘回归的NIRS校准模型能够确定有残茬或无残茬土壤中的δ（13）C，有残茬土壤的多重相关系数为0.81，预测标准误差为千分之0.5，无残茬土壤的多重相关系数为0.92，预测标准误差为千分之0.2。土壤中δ（13）C量化的比率性能偏差，有残茬土壤为2.5，无残茬土壤为3.8。这表明该模型足以确定-16.2‰至-20.4‰范围内未知土壤的δ（13）C。近红外校准的发展使得能够在更短的时间内，通过将远程反射光纤探头应用于土壤样品，采用无损方法分析测定未知农业土壤中δ（13）C的值。
