Infrared spectroscopy as a tool for the assessment of soil biological quality in agricultural soils under contrasting management practices

被引:24
作者
Comino, F. [1 ]
Aranda, V [2 ]
Garcia-Ruiz, R. [3 ]
Ayora-Canada, M. J. [1 ]
Dominguez-Vidal, A. [1 ]
机构
[1] Univ Jaen, Dept Phys & Analyt Chem, Campus Las Lagunillas S-N, Jaen 23071, Spain
[2] Univ Jaen, Soil Sci Sect, Dept Geol, Jaen, Spain
[3] Univ Jaen, Dept Anim & Plant Biol & Ecol, Ecol Sect, Jaen, Spain
关键词
NIR; Soil enzyme activity; Biological soil quality; Soil quality index; REFLECTANCE SPECTROSCOPY; BIOCHEMICAL-PROPERTIES; ENZYME-ACTIVITIES; PREDICTION; INDEXES;
D O I
10.1016/j.ecolind.2017.12.046
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Soil quality estimation is one of the most important means of evaluating changes in soil resulting from management. However, there is still no unanimity about what parameters should be included in soil quality assessment. Although there is a consensus on the inclusion of biological variables, mainly because they are robust and tend to show a short-term response after disturbances, their measurement is usually expensive and time consuming. This study explored the feasibility of using infrared spectroscopy for estimating biological parameters in olive grove soils under organic and conventional management. Four types of soils in two areas with contrasting parent material (marls and colluvial limestones) in southern Spain were selected. Biological status was established by measuring soil enzyme activities related to nutrient cycling (acid phosphatase, alkaline phosphatase, beta-glucosidase, arylsulfatase and dehydrogenase) and potential nitrification rate, and calculating their geometric mean as the GMea index. The infrared spectroscopic signature of the soil proved to be sensitive to biological status, and discriminated the different types of soil, which had quite different biological activity, relatively well (sensitivity and specificity over 97%), but did not discriminate different soil management practices quite as well (sensitivity and specificity over 75%). In addition, the results acceptably predicted the biological GMea index (RPD = 2) from near infrared (NIR) spectra by means of partial least squares (PIS) regression. These results demonstrate the applicability of infrared spectroscopy as a fast and efficient technique for estimating biological soil quality, as well as for discriminating between soils with differing biological quality.
引用
收藏
页码:117 / 126
页数:10
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