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Balancing machine learning and artificial intelligence in soil science with human perspective and experience

Pedosphere 2024年第1期34卷 9-12页

作者： David C.WEINDORF somsubhra chakraborty Department of Earth and Atmospheric Science Central Michigan Universityount Pleasant M148859USA Agricultural and Food Engineering Department Indian Institute of TechnologyKharagpur 721302India

Machine learning and artificial intelligence continue to evolve at a rapid pace, with many potential applications related to soil science. Even so, human experience and perception play an invaluable role in characterizing soil properties, especially qualitative properties that may elude sensing/computer-based modeling approaches. The elegant solution to this conundrum relies on the synthesis of computer-aided predictive modeling with human insight and *** global population surpasses 8 billion, the importance of optimized agronomic production to feed a hungry world has never been more important.

关键词： soil elude qualitative

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维普期刊数据库

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Selection of Rice Genotypes for Salinity Tolerance Through Morpho-Biochemical Assessment

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Rice science 2014年第5期21卷 288-298页

作者： Md. Nasim ALI Bhaswati GHOSH Saikat GANTAIT somsubhra chakraborty Department of Agricultural Biotechnology Faculty Centre for Integrated Rural Development and Management School of Agriculture and Rural Development Ramakrishna Mission Vivekananda UniversityRamakrishna Mission Ashrama NarendrapurKolkata 700103 India Department of Crop Science Faculty of Agriculture University Putra Malaysia43400 Serdang SelangorMalaysia Sasya Shyamala Krishi Vigyan Kendra Ramakrishna Mission Vivekananda UniversityArapanch Sonarpur Kolkata 700150 India

The present study reported the morpho-biochemical evaluation of 15 selected rice genotypes for salt tolerance at the seedling stage. Growth parameters including shoot length, root length, plant biomass, plant turgid weight, plant dry weight along with relative water content were measured after exposure to saline solution （with electrical conductivity value of 12 dS/m）. Genotypes, showing significant differential responses towards salinity in the fields, were assessed through 14 salinity-linked morpho-biochemical attributes, measured at 14 d after exposure of seedling in saline nutrient solution. Relative water content, chlorophyll a/b, peroxidase activity and plant biomass were identified as potential indicators of salt tolerance. Principal component analysis and successive Hierarchical clustering using Euclidean distance revealed that Talmugur, Gheus, Ghunsi, Langalmura, Sabitapalui, and Sholerpona were promising genotypes for further breeding programmes in rice. The maximum Euclidean distance was plotted between Thavallakanan and Talmugur （7.49）, followed by Thavallakanan and Langalmura （6.82）, indicating these combinations may be exploited as parental lines in hybridization programmes to develop salinity tolerant variety.

关键词： chlorophyll content electrical conductivity Oryza sativa L. peroxidase activity prolinecontent relative water content salinity tolerance sugar content superoxide dismutase

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维普期刊数据库

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In-Situ Differentiation of Acidic and Non-Acidic Tundra via Portable X-ray Fluorescence (PXRF) Spectrometry

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Pedosphere 2016年第4期26卷 549-560页

作者： somsubhra chakraborty David C. WEINDORF GARY J. MICHAELSON Chien Lu PING Ashok CHOUDHURY Tarek KANDAKJI Autumn ACREE Akriti SHARMA WANG Dandan Uttar Banga Krishi Viswavidyalaya Cooch Behar 736165 Department of Plant and Soil Science Texas Tech University Lubbock TX 79409 University of Alaska Fairbanks Palmer Research Center Palmer AK 99645 Louisiana State University Agricultural Center Baton Rouge LA 70803 College of Geography and Remote Sensing Nanjing University of Information Science and Technology Nanjing 210044

Frozen soils or those with permafrost cover large areas of the earth's surface and support unique vegetative ecosystems. Plants growing in such harsh conditions have adapted to small niches, which allow them to survive. In northern Alaska, USA, both moist acidic and non-acidic tundra occur, yet determination of frozen soil p Hs currently requires thawing of the soil so that electrometric pH methods can be utilized. Contrariwise, a portable X-ray fluorescence(PXRF) spectrometer was used in this study to assess elemental abundances and relate those characteristics to soil pH through predictive multiple linear regressions. Two operational modes, Soil Mode and Geochem Mode, were utilized to scan frozen soils in-situ and under laboratory conditions, respectively, after soil samples were dried and ground. Results showed that lab scanning produced optimal results with adjusted coefficient of determination(R^2) of 0.88 and 0.33 and root mean squared errors(RMSEs) of 0.87 and 0.34 between elemental data and lab-determined pH for Soil Mode and Geochem Mode, respectively. Even though the presence of ice attenuated fluoresced radiation under field conditions, adjusted R^2 and RMSEs between the datasets still provided reasonable model generalization(e.g., 0.73 and 0.49 for field Geochem Mode). Principal component analysis qualitatively separated multiple sampling sites based on elemental data provided by PXRF, reflecting differences in the chemical composition of the soils studied. Summarily, PXRF can be used for in-situ determination of soil pH in arctic environments without the need for sample modification and thawing. Furthermore, use of PXRF for determination of soil pH may provide higher sample throughput than traditional eletrometric-based methods, while generating elemental data useful for the prediction of multiple soil parameters.

关键词： X射线荧光光谱仪原位测定非酸性便携式苔原土壤pH值多元线性回归分析地球化学模式

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