scholarly journals Soil quality and its implication for brackishwater pond soil management option in East Java Province, Indonesia

2021 ◽  
Vol 860 (1) ◽  
pp. 012037
Author(s):  
Akhmad Mustafa ◽  
Erna Ratnawati
Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 650
Author(s):  
Jesús Aguilera-Huertas ◽  
Beatriz Lozano-García ◽  
Manuel González-Rosado ◽  
Luis Parras-Alcántara

The short- and medium—long-term effects of management and hillside position on soil organic carbon (SOC) changes were studied in a centenary Mediterranean rainfed olive grove. One way to measure these changes is to analyze the soil quality, as it assesses soil degradation degree and attempts to identify management practices for sustainable soil use. In this context, the SOC stratification index (SR-COS) is one of the best indicators of soil quality to assess the degradation degree from SOC content without analyzing other soil properties. The SR-SOC was calculated in soil profiles (horizon-by-horizon) to identify the best soil management practices for sustainable use. The following time periods and soil management combinations were tested: (i) in the medium‒long-term (17 years) from conventional tillage (CT) to no-tillage (NT), (ii) in the short-term (2 years) from CT to no-tillage with cover crops (NT-CC), and (iii) the effect in the short-term (from CT to NT-CC) of different topographic positions along a hillside. The results indicate that the SR-SOC increased with depth for all management practices. The SR-SOC ranged from 1.21 to 1.73 in CT0, from 1.48 to 3.01 in CT1, from 1.15 to 2.48 in CT2, from 1.22 to 2.39 in NT-CC and from 0.98 to 4.16 in NT; therefore, the soil quality from the SR-SOC index was not directly linked to the increase or loss of SOC along the soil profile. This demonstrates the time-variability of SR-SOC and that NT improves soil quality in the long-term.


Soil Research ◽  
2004 ◽  
Vol 42 (7) ◽  
pp. 793 ◽  
Author(s):  
Teklu Erkossa ◽  
Karl Stahr ◽  
Thomas Gaiser

The study was conducted at Caffee Doonsa (08°88′N, 39°08′E; 2400 m asl), a small watershed in the central highlands of Ethiopia, in order to identify farmers’ goals of soil management and the indicators they use in selecting soils for a certain function, and to categorise the soils in different quality groups with respect to the major functions. Thirty-six male farmers of different age and wealth groups participated in a Participatory Rural Appraisal technique. They listed and prioritised 12 soil functions in the area and itemised the soil quality indicators (characteristics). Based on the indicators, the soils in the watershed were classified into 3 soil quality (SQ) groups (Abolse, Kooticha, and Carii). The SQ groups have been evaluated and ranked for the major soil functions. For crop production, Abolse was graded best, followed by Kooticha and Carii, respectively. The grain and straw yield data of wheat (Triticum aestivum L.) taken from the SQ groups confirmed the farmers claim, in that Abolse gave the highest grain yield (4573 kg/ha), followed by 4411 and 3657 kg/ha for Kooticha and Carii, respectively. Local insights should be included in systematic soil quality assessment, and in planning and implementation of various soil management interventions.


2016 ◽  
Vol 80 (1) ◽  
pp. 215-226 ◽  
Author(s):  
Maurício R. Cherubin ◽  
Douglas L. Karlen ◽  
André L.C. Franco ◽  
Carlos E. P. Cerri ◽  
Cássio A. Tormena ◽  
...  

2008 ◽  
Vol 19 (5) ◽  
pp. 516-529 ◽  
Author(s):  
R. E. Masto ◽  
P. K. Chhonkar ◽  
T. J. Purakayastha ◽  
A. K. Patra ◽  
D. Singh

2019 ◽  
Vol 281 ◽  
pp. 100-110 ◽  
Author(s):  
Felipe Bonini da Luz ◽  
Vanderlei Rodrigues da Silva ◽  
Fábio Joel Kochem Mallmann ◽  
Carlos Augusto Bonini Pires ◽  
Henrique Debiasi ◽  
...  

2016 ◽  
Vol 51 (9) ◽  
pp. 1643-1651 ◽  
Author(s):  
Diane Cristina Stefanoski ◽  
Cícero Célio de Figueiredo ◽  
Glenio Guimarães Santos ◽  
Robélio Leandro Marchão

Abstract The objective of this work was to assess soil quality indicators obtained with different datasets to compare soil management systems in the Brazilian Cerrado. Three criteria were used to select soil physical, chemical, and biological indicators: the full set of indicators obtained, with 36 parameters, for which all the physical, chemical, and biological soil properties were determined; a subset of indicators selected by principal component analysis (20 parameters); and a subset of indicators with some frequency of use in the literature (16 parameters). These indicators were obtained from the following management systems: no-tillage, conventional tillage, and native cerrado vegetation. Soil samples were collected at 0.0-0.1-m soil depth, and soil quality indicators were subjected to analysis of variance and their means were compared. The incorporation of soil native cerrado into agriculture decreased soil quality. The most commonly used indicators in the scientific literature are sensitive enough to detect differences in soil quality according to land use. Therefore, the selection of a minimum set of representative data can be more useful than a complex set of properties to compare management systems as to their soil quality.


Author(s):  
Stamatis Stamatiadis ◽  
A. Liopa-Tsakalidi ◽  
L. M. Maniati ◽  
P. Karageorgou ◽  
E. Natioti

2013 ◽  
Vol 120 (1-4) ◽  
pp. 1-13
Author(s):  
D. L. KARLEN ◽  
C. D. NANCE ◽  
D. L. DINNES ◽  
D. W. MEEK

The Soil Management Assessment Framework (SMAF) was developed to help quantify soil quality/health effects of tillage, crop rotation, and other soil management practices. Our objective was to determine if the SMAF could detect soil health differences after growing a single winter triticale (X Triticosecale Wittmack) crop. Soil samples were collected from 0 to 7.5- and 7.5 to 15-cm depth increments during the 2003 – 2004 and 2004 – 2005 growing seasons near Ames and Lewis, IA, and analyzed for several potential soil quality indicators. The SMAF analysis showed higher soil quality ratings for surface than subsurface samples. It also showed that a single winter grain crop can significantly improve soil quality after either corn (Zea mays L.) or soybean (Glycine max [L.] Merr.). Finally, in response to increasing interest in soil health assessments, a detailed appendix is attached to provide guidance for future soil health assessments.


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