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http://krishi.icar.gov.in/jspui/handle/123456789/44703
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Debarati Bhaduri, Tapan Jyoti Purakayastha, Pragati Pramanik, Ajoy Saha, Bibhash Chandra Verma, Mohammad Shahid, Debasish Saha | en_US |
dc.date.accessioned | 2021-01-12T11:02:55Z | - |
dc.date.available | 2021-01-12T11:02:55Z | - |
dc.date.issued | 2020-04-01 | - |
dc.identifier.citation | Bhaduri, D., Purakayastha, T. J., Pramanik, P., Saha, A., Verma, B. C., Shahid, M., & Saha, D. (2020). Indexing Methods of Soil Quality in Agro-Ecosystems: An Overview of Indian Soils and Beyond. In Soil Analysis: Recent Trends and Applications (pp. 255-284). Springer, Singapore. | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/44703 | - |
dc.description | Not Available | en_US |
dc.description.abstract | Soil quality research has been started in late 1990s to early 2000 in different parts of the world. The initial understanding was tough and confined to a group of researchers only as revealed from the publications, but slowly the interest was engulfed among soil scientists. Different authors define soil quality in number of ways. Soil quality is not limited to particular parameters or attributes hence it is difficult to calculate the soil quality in a simple step. To assess soil quality there is a need of soil quality index (SQI) which is the function of indicators termed as soil quality indicators. Mostly the SQIs are aimed to particular problems like soil erosion, soil pollution and soil nutrient depletion, crop production and productivity, etc. To identify the best suitable indicators there are few simple but important steps to keep in mind, like level of significance for various soil indicators as influenced by various management practices, cropping system, etc., selecting the representative minimum data set (MDS) with the help of suitable statistical techniques, correlation analysis among soil variables to reduce spurious grouping among highly weighted variables, scoring of the minimum data set indicators, and finally the computation of soil quality index. Here in this review we have discussed various progresses made so far, mostly in various Indian conditions. A vivid description of SQI developed under various agro-ecosystems (including cereal, pulse, horticultural and value added crops like cotton, tea, medicinal plants) has been emphasized along with spatial approaches for SQI and the effect of ecosystems on SQI. The understanding of SQI is bit complex, but considering the immense possibility of this useful concept and progression required in future, we trust this compilation will serve a beneficial document for the years to come. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | Springer Nature Singapore Pte Ltd. 2020 | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | Soil quality | en_US |
dc.subject | Sustainable agriculture | en_US |
dc.subject | Soil quality index | en_US |
dc.subject | Indexing approaches | en_US |
dc.subject | Soil health | en_US |
dc.subject | Ecosystems | en_US |
dc.subject | Climate change | en_US |
dc.title | Indexing Methods of Soil Quality in Agro-Ecosystems: An Overview of Indian Soils and Beyond | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Book chapter | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Soil Analysis: Recent Trends and Applications [A. Rakshit et al. (eds.)] | en_US |
dc.publication.volumeno | Not Available | en_US |
dc.publication.pagenumber | 255-284 | en_US |
dc.publication.divisionUnit | Crop Production Division | en_US |
dc.publication.sourceUrl | https://doi.org/10.1007/978-981-15-2039-6_14 | en_US |
dc.publication.authorAffiliation | ICAR::National Rice Research Institute | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
Appears in Collections: | CS-NRRI-Publication |
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