scholarly journals Quality soil management or soil quality management : performance versus semantics

Author(s):  
R.E Sojka ◽  
D.R Upchurch ◽  
N.E Borlaug
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 ◽  
...  

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rose Clancy ◽  
Dominic O'Sullivan ◽  
Ken Bruton

PurposeData-driven quality management systems, brought about by the implementation of digitisation and digital technologies, is an integral part of improving supply chain management performance. The purpose of this study is to determine a methodology to aid the implementation of digital technologies and digitisation of the supply chain to enable data-driven quality management and the reduction of waste from manufacturing processes.Design/methodology/approachMethodologies from both the quality management and data science disciplines were implemented together to test their effectiveness in digitalising a manufacturing process to improve supply chain management performance. The hybrid digitisation approach to process improvement (HyDAPI) methodology was developed using findings from the industrial use case.FindingsUpon assessment of the existing methodologies, Six Sigma and CRISP-DM were found to be the most suitable process improvement and data mining methodologies, respectively. The case study revealed gaps in the implementation of both the Six Sigma and CRISP-DM methodologies in relation to digitisation of the manufacturing process.Practical implicationsValuable practical learnings borne out of the implementation of these methodologies were used to develop the HyDAPI methodology. This methodology offers a pragmatic step by step approach for industrial practitioners to digitally transform their traditional manufacturing processes to enable data-driven quality management and improved supply chain management performance.Originality/valueThis study proposes the HyDAPI methodology that utilises key elements of the Six Sigma DMAIC and the CRISP-DM methodologies along with additions proposed by the author, to aid with the digitisation of manufacturing processes leading to data-driven quality management of operations within the supply chain.


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

Sign in / Sign up

Export Citation Format

Share Document