Development of a soil quality index to evaluate agricultural cropping systems in southern Brazil

2022 ◽  
Vol 218 ◽  
pp. 105293
Author(s):  
Luis Fernando Marion ◽  
Robson Schneider ◽  
Maurício Roberto Cherubin ◽  
Gustavo Stolzenberg Colares ◽  
Patrik Gustavo Wiesel ◽  
...  
Author(s):  
Cevdet Şeker ◽  
Hasan Hüseyin Özaytekin ◽  
Hamza Negiş ◽  
İlknur Gümüş ◽  
Mert Dedeoğlu ◽  
...  

Author(s):  
J. A. Sofi ◽  
A. G. Bhat ◽  
N. A. Kirmai ◽  
J. A. Wani ◽  
Aabid H. Lone ◽  
...  

2018 ◽  
Vol 64 (13) ◽  
pp. 1892-1909 ◽  
Author(s):  
Quintino Araujo ◽  
Dario Ahnert ◽  
Guilherme Loureiro ◽  
José Faria ◽  
Cinira Fernandes ◽  
...  

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

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