Moscow University Soil Science Bulletin最新文献_第5页

Achievements and Prospects for Advancement of Soil Microbiology at Moscow State University 莫斯科国立大学土壤微生物学的成就和发展前景

Moscow University Soil Science Bulletin Pub Date : 2023-12-01 DOI: 10.3103/s0147687423040087

A. L. Stepanov, N. A. Manucharova, D. A. Nikitin, M. V. Semenov

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The Effect of Long-Term Use of Organic and Mineral Fertilizers on the Agrochemical Properties of Soddy–Podzolic Soil and the Productivity of Perennial Grasses in Forage Culture in the European North 长期施用有机肥和矿物肥对欧洲北部稻田土壤的农化特性和多年生牧草产量的影响

Moscow University Soil Science Bulletin Pub Date : 2023-12-01 DOI: 10.3103/s0147687423060029

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Use of NIRS in Soil Properties Evaluation Related to Soil Salinity and Sodicity in Colombian Caribbean Coast 利用近红外光谱技术评估哥伦比亚加勒比海沿岸与土壤盐碱度相关的土壤特性

Moscow University Soil Science Bulletin Pub Date : 2023-12-01 DOI: 10.3103/s0147687423050046

{"title":"Use of NIRS in Soil Properties Evaluation Related to Soil Salinity and Sodicity in Colombian Caribbean Coast","authors":"","doi":"10.3103/s0147687423050046","DOIUrl":"https://doi.org/10.3103/s0147687423050046","url":null,"abstract":" <h3>Abstract</h3> The banana sector contributes to 3% of the Colombia total exports, becoming the most important crop in the north of the country, benefiting more than 2.5 million families. Banana production is concentrated on the Colombian Caribbean coast where most of 90% of the soils are affected to some degree of salt affection in soils. This study was carried out in the municipality of Zona Bananera, Department of Magdalena (Colombia) elsewhere eleven geomorphological units were delimited through geomorphological surveying with geopedological methods. Given the high costs of implementing salt monitoring and management programs in the field, the implementation of Near Infrared spectroscopy (NIR) and image analysis are proposed as an alternative for mapping soils salt affectation. Geostatistical methods, traditional soil laboratory methods and multispectral analysis of 697 soil samples were analyzing using machine learning and spectral models. The Orthogonal Partial Linear Square- Discriminant Analyses (OPLS-DA), Principal Component Regression (PCR), Partial Linear Square (PLS–PLSR), Least Absolute Shrinkage and Selection Operator (LASSO) were implemented. Soil cartographies for SAS were designed in areas under banana cultivation, determining the affectation degree. The results obtained showed that 45.1% of the soils are affected by salts, with R2 0.76 and RMS 0.15 for the applied of supervised models. OPLS-DA had a better performance being the high above sea level was the principal covariable to improve the model accuracy. LASSO and PLS were useful to Mg+2 and K+ with RMSE 0.92 and 0.34 and R2 of 0.37 and 0.44, while Saitsky&Golay filter improved the predictions model for pH and Ca+2. The use of combined techniques of geopedology, geostatistics and spectroscopy were efficient, practical and cheap methodologies for evaluate soil properties associate to SAS in the stablished banana crops. ","PeriodicalId":501690,"journal":{"name":"Moscow University Soil Science Bulletin","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139580073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sola Incognita: Unsolved Problems of Genetic Soil Science 独孤求败：尚未解决的遗传土壤学问题

Moscow University Soil Science Bulletin Pub Date : 2023-12-01 DOI: 10.3103/s0147687423040026

P. V. Krasilnikov

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Erratum to: A Comparative Characterization of the Soils and Plant Cover of Tombolos on the Coasts of the White and Baltic Seas 勘误：白海和波罗的海沿岸通博卢土壤和植物覆盖的比较特征

Moscow University Soil Science Bulletin Pub Date : 2023-09-01 DOI: 10.3103/S0147687423330013

I. Bagdasarov, M. Tseits, Yu.A. Kryukova, K. Taskina, M. V. Konyushkova

引用次数: 0