Ruby Hume, Petra Marschner, Sean Mason, Rhiannon K. Schilling, Huajian Liu, Nathaniel Jewell, Christoper J. Brien, Luke M. Mosley
{"title":"利用高光谱成像技术评估小麦对土壤酸化和施肥的反应","authors":"Ruby Hume, Petra Marschner, Sean Mason, Rhiannon K. Schilling, Huajian Liu, Nathaniel Jewell, Christoper J. Brien, Luke M. Mosley","doi":"10.1007/s11104-024-07029-3","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background and aims</h3><p>Soil acidification can negatively affect agricultural production by reducing uptake of essential nutrients and increasing aluminium toxicity in crops. This study investigated whether hyperspectral imaging could accurately measure wheat response to soil acidification and subsequent remediation via liming.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>A high-throughput, automated greenhouse and hyperspectral imaging facility was used to evaluate differences between hyperspectral data of wheat plants in either acidic soil or soil that had been limed. Using RGB imaging and growth rate prediction, plant growth was measured to assess if it increased with lime application. The study also used partial least squares regression analysis (PLSR) to assess whether hyperspectral imaging could predict plant tissue nutrient concentration and indicate nutrient deficiencies and toxicities associated with soil acidity.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>Spectral differences were observed between plants in acidic and non-acidic soil around the end of tillering and beginning of stem elongation. The red edge spectral region contributed significantly to this difference and, when used in vegetation indices, confirmed increases in plant growth following lime application, observed via high throughput phenotypic analysis. PLSR analysis was ineffective in predicting nutrient concentration of plant tissue in this context, likely due to low concentrations of nutrients associated with acidification, limited sample size, and small variation in nutrient concentrations.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>Findings suggest that hyperspectral imaging could prove useful in the detection of soil acidification effects on wheat crops under contained controlled environmental conditions, and may, with further in-field testing, enable improved spatial mapping of paddocks to help remediate this significant agricultural issue.\n</p>","PeriodicalId":20223,"journal":{"name":"Plant and Soil","volume":"111 1","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing wheat responses to soil acidification and liming using hyperspectral imaging\",\"authors\":\"Ruby Hume, Petra Marschner, Sean Mason, Rhiannon K. Schilling, Huajian Liu, Nathaniel Jewell, Christoper J. Brien, Luke M. Mosley\",\"doi\":\"10.1007/s11104-024-07029-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Background and aims</h3><p>Soil acidification can negatively affect agricultural production by reducing uptake of essential nutrients and increasing aluminium toxicity in crops. This study investigated whether hyperspectral imaging could accurately measure wheat response to soil acidification and subsequent remediation via liming.</p><h3 data-test=\\\"abstract-sub-heading\\\">Methods</h3><p>A high-throughput, automated greenhouse and hyperspectral imaging facility was used to evaluate differences between hyperspectral data of wheat plants in either acidic soil or soil that had been limed. Using RGB imaging and growth rate prediction, plant growth was measured to assess if it increased with lime application. The study also used partial least squares regression analysis (PLSR) to assess whether hyperspectral imaging could predict plant tissue nutrient concentration and indicate nutrient deficiencies and toxicities associated with soil acidity.</p><h3 data-test=\\\"abstract-sub-heading\\\">Results</h3><p>Spectral differences were observed between plants in acidic and non-acidic soil around the end of tillering and beginning of stem elongation. The red edge spectral region contributed significantly to this difference and, when used in vegetation indices, confirmed increases in plant growth following lime application, observed via high throughput phenotypic analysis. PLSR analysis was ineffective in predicting nutrient concentration of plant tissue in this context, likely due to low concentrations of nutrients associated with acidification, limited sample size, and small variation in nutrient concentrations.</p><h3 data-test=\\\"abstract-sub-heading\\\">Conclusions</h3><p>Findings suggest that hyperspectral imaging could prove useful in the detection of soil acidification effects on wheat crops under contained controlled environmental conditions, and may, with further in-field testing, enable improved spatial mapping of paddocks to help remediate this significant agricultural issue.\\n</p>\",\"PeriodicalId\":20223,\"journal\":{\"name\":\"Plant and Soil\",\"volume\":\"111 1\",\"pages\":\"\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Plant and Soil\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1007/s11104-024-07029-3\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant and Soil","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1007/s11104-024-07029-3","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
Assessing wheat responses to soil acidification and liming using hyperspectral imaging
Background and aims
Soil acidification can negatively affect agricultural production by reducing uptake of essential nutrients and increasing aluminium toxicity in crops. This study investigated whether hyperspectral imaging could accurately measure wheat response to soil acidification and subsequent remediation via liming.
Methods
A high-throughput, automated greenhouse and hyperspectral imaging facility was used to evaluate differences between hyperspectral data of wheat plants in either acidic soil or soil that had been limed. Using RGB imaging and growth rate prediction, plant growth was measured to assess if it increased with lime application. The study also used partial least squares regression analysis (PLSR) to assess whether hyperspectral imaging could predict plant tissue nutrient concentration and indicate nutrient deficiencies and toxicities associated with soil acidity.
Results
Spectral differences were observed between plants in acidic and non-acidic soil around the end of tillering and beginning of stem elongation. The red edge spectral region contributed significantly to this difference and, when used in vegetation indices, confirmed increases in plant growth following lime application, observed via high throughput phenotypic analysis. PLSR analysis was ineffective in predicting nutrient concentration of plant tissue in this context, likely due to low concentrations of nutrients associated with acidification, limited sample size, and small variation in nutrient concentrations.
Conclusions
Findings suggest that hyperspectral imaging could prove useful in the detection of soil acidification effects on wheat crops under contained controlled environmental conditions, and may, with further in-field testing, enable improved spatial mapping of paddocks to help remediate this significant agricultural issue.
期刊介绍:
Plant and Soil publishes original papers and review articles exploring the interface of plant biology and soil sciences, and that enhance our mechanistic understanding of plant-soil interactions. We focus on the interface of plant biology and soil sciences, and seek those manuscripts with a strong mechanistic component which develop and test hypotheses aimed at understanding underlying mechanisms of plant-soil interactions. Manuscripts can include both fundamental and applied aspects of mineral nutrition, plant water relations, symbiotic and pathogenic plant-microbe interactions, root anatomy and morphology, soil biology, ecology, agrochemistry and agrophysics, as long as they are hypothesis-driven and enhance our mechanistic understanding. Articles including a major molecular or modelling component also fall within the scope of the journal. All contributions appear in the English language, with consistent spelling, using either American or British English.