[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127902-en":3,"doc-seo-127902-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},127902,137451207643,"Noah","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","Analyzing soil enzymes to assess soil quality parameters in long-term copper accumulation through a machine learning approach","Soil contamination by agrochemicals poses a major risk to soil health and ecosystem functioning, especially for heavy metals such as copper that persist and accumulate over time. While laboratory spiking experiments clarify acute toxicity, they often fail to represent chronic, field-relevant dynamics in living agroecosystems. This study applies multivariate data analysis and machine learning to link long-term Cu accumulation to soil extracellular enzymatic activities and microbial functionality using 315 samples from 21 apple orchards in South Tyrol, Italy. Results indicate Cu affects phosphatase activity above 60 mg kg−1 available Cu, while protease activity correlates positively with Cu and soil organic matter and management mainly influence carbon-cycle enzymes, informing potential phosphorus-cycle disruption and plant nutrition.","Applied Soil Ecology 195 (2024) 105261  \nContents lists available at ScienceDirect  \nApplied Soil Ecology  \njournal [homepage:](homepage: www.elsevier.com/locate/apsoil)[ www.elsevier.com/locate/apsoil](homepage: www.elsevier.com/locate/apsoil)  \n| Analyzing soil enzymes to assess soil quality parameters in long-term copper accumulation through a machine learning approach |  |  |  |\n| --- | --- | --- | --- |\n| G. Genova a, b, f, L. Borruso a, *, M. Signorini a, M. Mitterera, G. Niedrist b, S. Cesco a, B. Felderer d, L. Cavanie, T. Mimmoa, c\u003Cbr>a Free University of Bolzano, Faculty of Agricultural, Environmental and Food Sciences, Bolzano/Bozen, Italy\u003Cbr>b Eurac Research, Institute for Alpine Environment, Bolzano/Bozen, Italy c Competence Centre for Plant Health, Free University of Bolzano, Bolzano/Bozen, Italy d Ecorecycling Felderer, Lana, Italy\u003Cbr>e Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy f ISRIC – World Soil Information, Wageningen, the Netherlands |  |  |  |\n| A R T I C L E I N F O |  | A B S T R A C T |  |\n| Keywords:\u003Cbr>Machine learning Extracellular enzyme activity Microbial functionality\u003Cbr>Soil ecology\u003Cbr>Copper\u003Cbr>Apple orchards\u003Cbr>Long-term accumulation |  | Soil contamination by agrochemicals is a big concern for soil health and ecosystem functioning. This is especially true for non-degradable substances like heavy metals (HM) that, because of their long-term use, are reaching significant values today due to soil accumulation. Among agrochemicals, copper (Cu) has been important infighting fungal diseases on perennial crops for centuries.\u003Cbr>Laboratory experiments can be useful to understand the highest potential toxic effect of Cu but need to reflect what happens with long-term application in a dynamic and living agroecosystem. This study uses multivariate data analysis and machine learning to investigate long-term Cu accumulation on soil quality parameters, especially soil extracellular enzymatic activities. We collected soil samples from 21 apple orchards in South Tyrol, Italy. The orchards had different concentrations of Cu. We took 315 samples in total and analyzed them for various soil properties. We also measured the concentrations of elements in apple leaves and the activities of soil extracellular enzymes. We depicted the effect of Cu on several enzymatic activities, shedding light on the effect of Cu on the soil microbial communities functionality. Our results show that Cu concentrations in the study area affect only phosphatase activity, showing effects above 60 mg kg − 1 of available Cu. Protease activity was positively correlated with Cu, while soil organic matter and management mainly influenced the carbon (C) cycle enzymes. Phosphatase decrease could be of concern for the potential disruption of the Phosphorus (P) cycle in the soil and plays a role in plant nutrition, as seen by P concentration in apple trees' leaves.\u003Cbr>We demonstrated how machine learning can help interpret complex and multivariate environmental data and overcome some downsides of traditional statistical models. |  |\n\n1. Introduction  \nSoil degradation resulting from agricultural practices, such as the use of pesticides and fertilizers, is a growing concern due to the presence of heavy metals (HMs) (Guo et al., 2018; Panagos et al., 2018). Many pesticides that were widely used in the past and are still used today contain high levels of metals (e.g., Mancozeb (National Center for Biotechnology Information, 2021)). For example, copper (Cu) containing fungicides such as Bordeaux mixture (Cu sulfate) and Cu oxychloride have been used to protect perennial crops from infections (Cesco et al., 2021). Nevertheless, HMs contamination, mainly Cu, can affect soil  \nbiodiversity particularly by reducing the soil microbial enzyme activities (Karimi et al., 2021; Signorini et al., 2023). As a result, soil enzymes are widely used as indicators of soil health due to their strong correlation with soil qual","cbCaiusiLtLUchDQ","https://ap.wps.com/l/cbCaiusiLtLUchDQ","pdf",7860845,3,1,11,"English","en",105,"# Introduction\n## Background: heavy metals and copper in agriculture\n## Soil enzymes as indicators of soil health\n## Limitations of enzyme assays and need for complementary measurements\n## Rationale for long-term accumulation and machine learning approach","[{\"question\":\"Why is long-term copper accumulation a concern for soil health?\",\"answer\":\"Copper is a non-degradable heavy metal that can build up in soil over years of agrochemical use, impacting ecosystem functioning and soil biology.\"},{\"question\":\"How were soil extracellular enzymes and microbial functionality assessed in this study?\",\"answer\":\"Soil samples from 21 apple orchards were analyzed for soil properties and extracellular enzyme activities, and machine learning was used to interpret how Cu levels relate to microbial functionality.\"},{\"question\":\"What enzyme responses were most affected by copper concentrations?\",\"answer\":\"Copper concentrations influenced phosphatase activity, with effects observed above 60 mg kg−1 available Cu, while protease activity showed a positive correlation with Cu.\"}]","Analyzing soil enzymes to assess soil quality parameters in long-term copper accumulation through a machine learning approach | 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is long-term copper accumulation a concern for soil health?","Question",{"text":76,"@type":77},"Copper is a non-degradable heavy metal that can build up in soil over years of agrochemical use, impacting ecosystem functioning and soil biology.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How were soil extracellular enzymes and microbial functionality assessed in this study?",{"text":81,"@type":77},"Soil samples from 21 apple orchards were analyzed for soil properties and extracellular enzyme activities, and machine learning was used to interpret how Cu levels relate to microbial functionality.",{"name":83,"@type":74,"acceptedAnswer":84},"What enzyme responses were most affected by copper concentrations?",{"text":85,"@type":77},"Copper concentrations influenced phosphatase activity, with effects observed above 60 mg kg−1 available Cu, while protease activity showed a positive correlation with 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