Albrecht Benzing, Hans-Peter Piepho, Ryan Orr, Juan-Carlos Ullauri
{"title":"有机香蕉生产中氮肥用量对产量回归偏差的检测","authors":"Albrecht Benzing, Hans-Peter Piepho, Ryan Orr, Juan-Carlos Ullauri","doi":"10.1002/jpln.12009","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background and aims</h3>\n \n <p>Bananas are demanding in nitrogen (N) input; therefore, there is a temptation for organic farmers for using synthetic N fertilisers, which are not allowed under organic standards. The aim of our study was to develop a tool that identifies high banana yields obtained with suspiciously low organic N input.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We systematically reviewed literature from experimental studies on N fertilisation in bananas from all over the world. We also developed a simplified N balance model for organic bananas. Furthermore, N fertilisation and banana yield data from organic and conventional farmers in different countries were collected. From these, a subset of trustworthy organic farms was identified, as a reference concerning plausible ratios of yield versus fertilisation. A model was developed to estimate the deviation from the regression of trustworthy farms and thus identify suspicious cases.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Neither literature nor the N balance led to a meaningful benchmark for differentiating plausible from non-plausible yields. The regression of yield on N fertiliser rate from the trustworthy organic farmers, however, turned out to be a helpful reference, and the deviation from this regression helps to achieve our aim. Depending on the alert limit, that is, the probability of obtaining false positive results, 4, 6, or 9 out of 157 data-pairs from organic farmers turned out to be suspicious.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>Measuring deviation from the regression of the trustworthy farms is a useful tool for identifying organic banana farmers suspected to be using synthetic N fertilisers but is not in itself a proof of fraud. The model will improve as more data becomes available.</p>\n </section>\n </div>","PeriodicalId":16802,"journal":{"name":"Journal of Plant Nutrition and Soil Science","volume":"188 4","pages":"604-615"},"PeriodicalIF":2.8000,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jpln.12009","citationCount":"0","resultStr":"{\"title\":\"Deviation From the Regression of Yield on Nitrogen Fertiliser Rate as a Tool for Detecting Fraud in Organic Banana Production\",\"authors\":\"Albrecht Benzing, Hans-Peter Piepho, Ryan Orr, Juan-Carlos Ullauri\",\"doi\":\"10.1002/jpln.12009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background and aims</h3>\\n \\n <p>Bananas are demanding in nitrogen (N) input; therefore, there is a temptation for organic farmers for using synthetic N fertilisers, which are not allowed under organic standards. The aim of our study was to develop a tool that identifies high banana yields obtained with suspiciously low organic N input.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We systematically reviewed literature from experimental studies on N fertilisation in bananas from all over the world. We also developed a simplified N balance model for organic bananas. Furthermore, N fertilisation and banana yield data from organic and conventional farmers in different countries were collected. From these, a subset of trustworthy organic farms was identified, as a reference concerning plausible ratios of yield versus fertilisation. A model was developed to estimate the deviation from the regression of trustworthy farms and thus identify suspicious cases.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Neither literature nor the N balance led to a meaningful benchmark for differentiating plausible from non-plausible yields. The regression of yield on N fertiliser rate from the trustworthy organic farmers, however, turned out to be a helpful reference, and the deviation from this regression helps to achieve our aim. Depending on the alert limit, that is, the probability of obtaining false positive results, 4, 6, or 9 out of 157 data-pairs from organic farmers turned out to be suspicious.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>Measuring deviation from the regression of the trustworthy farms is a useful tool for identifying organic banana farmers suspected to be using synthetic N fertilisers but is not in itself a proof of fraud. 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Deviation From the Regression of Yield on Nitrogen Fertiliser Rate as a Tool for Detecting Fraud in Organic Banana Production
Background and aims
Bananas are demanding in nitrogen (N) input; therefore, there is a temptation for organic farmers for using synthetic N fertilisers, which are not allowed under organic standards. The aim of our study was to develop a tool that identifies high banana yields obtained with suspiciously low organic N input.
Methods
We systematically reviewed literature from experimental studies on N fertilisation in bananas from all over the world. We also developed a simplified N balance model for organic bananas. Furthermore, N fertilisation and banana yield data from organic and conventional farmers in different countries were collected. From these, a subset of trustworthy organic farms was identified, as a reference concerning plausible ratios of yield versus fertilisation. A model was developed to estimate the deviation from the regression of trustworthy farms and thus identify suspicious cases.
Results
Neither literature nor the N balance led to a meaningful benchmark for differentiating plausible from non-plausible yields. The regression of yield on N fertiliser rate from the trustworthy organic farmers, however, turned out to be a helpful reference, and the deviation from this regression helps to achieve our aim. Depending on the alert limit, that is, the probability of obtaining false positive results, 4, 6, or 9 out of 157 data-pairs from organic farmers turned out to be suspicious.
Conclusion
Measuring deviation from the regression of the trustworthy farms is a useful tool for identifying organic banana farmers suspected to be using synthetic N fertilisers but is not in itself a proof of fraud. The model will improve as more data becomes available.
期刊介绍:
Established in 1922, the Journal of Plant Nutrition and Soil Science (JPNSS) is an international peer-reviewed journal devoted to cover the entire spectrum of plant nutrition and soil science from different scale units, e.g. agroecosystem to natural systems. With its wide scope and focus on soil-plant interactions, JPNSS is one of the leading journals on this topic. Articles in JPNSS include reviews, high-standard original papers, and short communications and represent challenging research of international significance. The Journal of Plant Nutrition and Soil Science is one of the world’s oldest journals. You can trust in a peer-reviewed journal that has been established in the plant and soil science community for almost 100 years.
Journal of Plant Nutrition and Soil Science (ISSN 1436-8730) is published in six volumes per year, by the German Societies of Plant Nutrition (DGP) and Soil Science (DBG). Furthermore, the Journal of Plant Nutrition and Soil Science (JPNSS) is a Cooperating Journal of the International Union of Soil Science (IUSS). The journal is produced by Wiley-VCH.
Topical Divisions of the Journal of Plant Nutrition and Soil Science that are receiving increasing attention are:
JPNSS – Topical Divisions
Special timely focus in interdisciplinarity:
- sustainability & critical zone science.
Soil-Plant Interactions:
- rhizosphere science & soil ecology
- pollutant cycling & plant-soil protection
- land use & climate change.
Soil Science:
- soil chemistry & soil physics
- soil biology & biogeochemistry
- soil genesis & mineralogy.
Plant Nutrition:
- plant nutritional physiology
- nutrient dynamics & soil fertility
- ecophysiological aspects of plant nutrition.