scholarly journals Quantifying the interactions of land management practices and agricultural productivity using a soil quality index

2017 ◽  
Vol 33 (4) ◽  
pp. 639-652 ◽  
Author(s):  
V. de Paul Obade
2019 ◽  
Vol 14 (1) ◽  
pp. 20
Author(s):  
Supriyadi Supriyadi ◽  
Widyatmani Sih Dewi ◽  
Desmiasari Nugrahani ◽  
Adila Azza Rahmah ◽  
Haryuni Haryuni ◽  
...  

Increased rice needs in an extensive use of paddy fields in the Jatipurno, Wonogiri. Managing rice fields can reduce soil quality. Proper management can improve soil quality, Jatipurno has management such as organic, semi-organic and inorganic paddy field management which have a real effect on soil quality. Assessment of soil quality is measured by physical, chemical and biological indicators, where each factor has a different effect. The chemical indicators are often used as the main indicators for determining soil quality, whereas every parameter has the opportunity to be the main indicator. So, biological indicators can play indicators. The main indicators are obtained from the correlation test (p-values ≤ 0,05 - < 0,01) and Principal Component Analysis with high value, eigenvalues > 1 have the potential to be used as Minimum Data Sets. The result is biological can be able to use as the Minimum Data Set such as microbial carbon biomass, respiration, and total bacterial colonies. The Soil Quality Index (SQI) of various paddy management practices shows very low to low soil quality values. The management of organic rice systems shows better Soil Quality Index with a score of 0,20 compared to other management. The practice of organic rice management shows that it can improve soil quality.


Author(s):  
Hiba Et-Tayeb ◽  
Khalid Ibno Namr ◽  
El Houssine El Mzouri ◽  
Bouchra El Bourhrami

2014 ◽  
Vol 79 (1) ◽  
pp. 224-238 ◽  
Author(s):  
Ted M. Zobeck ◽  
Jean L. Steiner ◽  
Diane E. Stott ◽  
Sara E. Duke ◽  
Patrick J. Starks ◽  
...  

Author(s):  
Vassilios Triantafyllidis ◽  
Achilleas Kontogeorgosa Chariklia Kosma ◽  
Angelos Patakas

Soil quality is a complex functional concept, which cannot be measured directly but only be inferred from both soil characteristics and cultivation practices. Among different approaches used, Soil Quality Index (SQI) is considered to be the most appropriate for quantitative assessment of soil quality. Since, there is no standard method for SQI estimation, the aim of this study is to identify soil quality parameters that could be used for the development of reliable SQI which could be effectively applied in Mediterranean ecosystems. Three different methods resulting in different SQIs were evaluated regarding their ability to monitor changes in agricultural soil properties over time. Overall, a set of soil’s parameters was used as soil health indicators (pH, CaCO3, EC, NO3-N, P, K, Mg, Cu, B, Zn, Fe, Mn, Silt, Clay, Sand and SOC) derived from 605 soil samples used to calculate the above SQIs. The most reliable SQI to distinguish the effect of the examined parameters was the weighted additive approach. These 16 soil indicators can be used as decision support tool for soil management practices, as well as indirect measures of soil function, serving to assess soil health for a sustainable Mediterranean agro-environment.


2004 ◽  
Vol 4 (3) ◽  
pp. 201-204 ◽  
Author(s):  
Giancarlo Barbiroli ◽  
Giovanni Casalicchio ◽  
Andrea Raggi

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1426
Author(s):  
Ahmed S. Abuzaid ◽  
Mohamed A. E. AbdelRahman ◽  
Mohamed E. Fadl ◽  
Antonio Scopa

Modelling land degradation vulnerability (LDV) in the newly-reclaimed desert oases is a key factor for sustainable agricultural production. In the present work, a trial for usingremote sensing data, GIS tools, and Analytic Hierarchy Process (AHP) was conducted for modeling and evaluating LDV. The model was then applied within 144,566 ha in Farafra, an inland hyper-arid Western Desert Oases in Egypt. Data collected from climate conditions, geological maps, remote sensing imageries, field observations, and laboratory analyses were conducted and subjected to AHP to develop six indices. They included geology index (GI), topographic quality index (TQI), physical soil quality index (PSQI), chemical soil quality index (CSQI), wind erosion quality index (WEQI), and vegetation quality index (VQI). Weights derived from the AHP showed that the effective drivers of LDV in the studied area were as follows: CSQI (0.30) > PSQI (0.29) > VQI (0.17) > TQI (0.12) > GI (0.07) > WEQI (0.05). The LDV map indicated that nearly 85% of the total area was prone to moderate degradation risks, 11% was prone to high risks, while less than 1% was prone to low risks. The consistency ratio (CR) for all studied parameters and indices were less than 0.1, demonstrating the high accuracy of the AHP. The results of the cross-validation demonstrated that the performance of ordinary kriging models (spherical, exponential, and Gaussian) was suitable and reliable for predicting and mapping soil properties. Integrated use of remote sensing data, GIS, and AHP would provide an effective methodology for predicting LDV in desert oases, by which proper management strategies could be adopted to achieve sustainable food security.


2021 ◽  
Vol 125 ◽  
pp. 107580
Author(s):  
Wuping Huang ◽  
Mingming Zong ◽  
Zexin Fan ◽  
Yuan Feng ◽  
Shiyu Li ◽  
...  

2015 ◽  
Vol 79 (6) ◽  
pp. 1629-1637 ◽  
Author(s):  
Vladimir Ivezić ◽  
Bal Ram Singh ◽  
Vlatka Gvozdić ◽  
Zdenko Lončarić

SOIL ◽  
2015 ◽  
Vol 1 (1) ◽  
pp. 173-185 ◽  
Author(s):  
R. Zornoza ◽  
J. A. Acosta ◽  
F. Bastida ◽  
S. G. Domínguez ◽  
D. M. Toledo ◽  
...  

Abstract. Soil quality (SQ) assessment has long been a challenging issue, since soils present high variability in properties and functions. This paper aims to increase the understanding of SQ through the review of SQ assessments in different scenarios providing evidence about the interrelationship between SQ, land use and human health. There is a general consensus that there is a need to develop methods to assess and monitor SQ for assuring sustainable land use with no prejudicial effects on human health. This review points out the importance of adopting indicators of different nature (physical, chemical and biological) to achieve a holistic image of SQ. Most authors use single indicators to assess SQ and its relationship with land uses – soil organic carbon and pH being the most used indicators. The use of nitrogen and nutrient content has resulted sensitive for agricultural and forest systems, together with physical properties such as texture, bulk density, available water and aggregate stability. These physical indicators have also been widely used to assess SQ after land use changes. The use of biological indicators is less generalized, with microbial biomass and enzyme activities being the most selected indicators. Although most authors assess SQ using independent indicators, it is preferable to combine some of them into models to create a soil quality index (SQI), since it provides integrated information about soil processes and functioning. The majority of revised articles used the same methodology to establish an SQI, based on scoring and weighting of different soil indicators, selected by means of multivariate analyses. The use of multiple linear regressions has been successfully used for forest land use. Urban soil quality has been poorly assessed, with a lack of adoption of SQIs. In addition, SQ assessments where human health indicators or exposure pathways are incorporated are practically inexistent. Thus, further efforts should be carried out to establish new methodologies to assess soil quality not only in terms of sustainability, productivity and ecosystem quality but also human health. Additionally, new challenges arise with the use and integration of stable isotopic, genomic, proteomic and spectroscopic data into SQIs.


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