Rapid diagnosis of agricultural soil health: A novel soil health index based on natural soil productivity and human management. (1st January 2021)

• Record Type: Journal Article
• Authors: Li, Zhuo; Lun, Fei; Liu, Ming; Xiao, Xiao; Wang, Chongyang; Wang, Linlin; Xu, Yueqing; Qi, Wei; Sun, Danfeng
• Is Part Of: Journal of environmental management. Volume 277(2021)
• Publication Date: 2021-01-01
• Subjects: Soil health -- Soil productivity -- NDVI time Series -- Principal component analysis; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2020.111402
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: It has become increasingly important to consider its productivity for agricultural soil health assessment. Moreover, one of the main challenges is that there are still few studies on addressing the complex dynamics of soil health assessment by the rapid and cross-regional method. Thus, we proposed a novel conceptual model to evaluate agricultural soil health in order to highlight the synergy and interaction of natural soil productivity and its external inputs; besides, the new proposed soil health index (SHI) can be used to rapidly quantify their influences of soil productivity on soil health assessment, based on the 10-day normalized difference vegetation index (NDVI) time series data. We applied the principal component analysis (PCA) to transform NDVI profiles into responses of crop primary productivity due to different drivers. The results demonstrated that soil productivity in our study area can be identified for different cropping systems by the PCA method; and different principle components (PCs) for the same cropping system can also be used to estimate contributions of natural soil productivity and human management productivity. The SHI indicator, defined by the equation of (PC1-PC2)/(PC1+PC2), was used to explore soil health in our study area. We found that soil in the orchard system was relatively healthier than that in other two cropping systems, indicating the natural soil productivity presented more contributions than that from external inputs. We concluded that it is useful to apply the SHI indicator into soil health assessment, especially considering the local natural situation and human management practices. Highlights: A rapid and cross-regional method was developed for soil health assessment. The principle is based on its inherent and external drivers of soil productivity. PCA was used with NDVI images to identify different drivers of soil productivity. SHI can illustrate the interaction between natural productivity and external inputs.