Example of the representation flag based on principal component analysis (PCA) and Q-statistics.

<p>In this example, samples from farmland soils (Massachusetts, USA) were evaluated against the NIR Neospectra OSSL model. All the test samples fell in the edge of the first two PCA spaces and were flagged as underrepresented regarding the full spectral feature space from the OSSL database. No...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	José L. Safanelli (20552654) (author)
مؤلفون آخرون:	Tomislav Hengl (623477) (author), Leandro L. Parente (20552657) (author), Robert Minarik (20552660) (author), Dellena E. Bloom (9227405) (author), Katherine Todd-Brown (20552663) (author), Asa Gholizadeh (693351) (author), Wanderson de Sousa Mendes (20552666) (author), Jonathan Sanderman (784692) (author)
منشور في:	2025
الموضوعات:	Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified widely used method training machine learning independent model evaluation global good initiative estimating soil properties study also presents centralized open resource representation flag ). soil spectroscopy community affordable soil data performing ml algorithm two spectral regions harmonizing several ssls soil spectroscopy spectral regions soil types opening data discusses several also subject spectral variations open resources open development ssls ). widespread adoption well predicted total sulfur scientific discovery reliable outputs refitting show predictive modeling prediction uncertainty prediction capacity new samples help bridge future development fold cross extractable sodium extractable nutrients exploratory analysis enable hundreds cubist comes conditions represented agricultural monitoring
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الوصف
الملخص:	<p>In this example, samples from farmland soils (Massachusetts, USA) were evaluated against the NIR Neospectra OSSL model. All the test samples fell in the edge of the first two PCA spaces and were flagged as underrepresented regarding the full spectral feature space from the OSSL database. Note: The Q-statistics method uses all the retained principal components (in our study, 120 components) for flagging underrepresented spectra, not only the first two components depicted in the illustration. Figure sourced from the OSSL Engine [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0296545#pone.0296545.ref066" target="_blank">66</a>].</p>

Example of the representation flag based on principal component analysis (PCA) and Q-statistics.

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