Small-Sample Authenticity Identification and Variety Classification of <i>Anoectochilus roxburghii</i> (Wall.) Lindl. Using Hyperspectral Imaging and Machine Learning.

Plants (Basel) · 2025 · PMC12030607 · PMID 40284066

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hedged sentence

0.0010

closest p · 0.0× alpha

0.0010

boldest claim

The sentences

highly significantp < 0.001actually significant

The analysis yielded an F-statistic of 298.59 and a p -value of approximately 9.03 × 10 −57 , indicating highly significant differences among model performances ( p < 0.001).

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Quoted from the open-access full text in Europe PMC under the licence the publisher applied. The sentence is reproduced exactly as published; the emphasis is ours.

Small-Sample Authenticity Identification and Variety Classification of &lt;i&gt;Anoectochilus roxburghii&lt;/i&gt; (Wall.) Lindl. Using Hyperspectral Imaging and Machine Learning.

The sentences

Small-Sample Authenticity Identification and Variety Classification of <i>Anoectochilus roxburghii</i> (Wall.) Lindl. Using Hyperspectral Imaging and Machine Learning.