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A novel random forest-based approach for the non-destructive and explainable estimation of ammonia and chlorophyll in fresh-cut rocket leaves

Stefano Polimena Gianvito Pio Maria Cefola Michela Palumbo Michelangelo Ceci Giovanni Attolico

Information Processing in Agriculture2025，Vol.12Issue(2)：P.221-231,11.

Information Processing in Agriculture2025，Vol.12Issue(2)：P.221-231,11.DOI:10.1016/j.inpa.2024.09.002

A novel random forest-based approach for the non-destructive and explainable estimation of ammonia and chlorophyll in fresh-cut rocket leaves

Stefano Polimena ¹Gianvito Pio ¹Maria Cefola ²Michela Palumbo ³Michelangelo Ceci ⁴Giovanni Attolico⁵

作者信息

1. Department of Computer Science,University of Bari Aldo Moro,Via E.Orabona 4,70125 Bari,Italy Big Data Laboratory,National Interuniversity Consortium for Informatics(CINI),Via Ariosto 25,00185 Rome,Italy
2. Institute of Sciences of Food Production,National Research Council of Italy,c/o CS-DAT,Via Michele Protano,71121 Foggia,Italy
3. Institute of Sciences of Food Production,National Research Council of Italy,c/o CS-DAT,Via Michele Protano,71121 Foggia,Italy Department of Science of Agriculture,Food and Environment,University of Foggia,Via Napoli 25,71122 Foggia,Italy
4. Department of Computer Science,University of Bari Aldo Moro,Via E.Orabona 4,70125 Bari,Italy Big Data Laboratory,National Interuniversity Consortium for Informatics(CINI),Via Ariosto 25,00185 Rome,Italy Department of Knowledge Technologies,Jožef Stefan Institute,Jamova cesta 39,1000,Ljubljana,Slovenia
5. Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing,National Research Council of Italy,via Amendola 122/D,70126,Bari,Italy
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摘要

关键词

Fresh-cut rocket leaves/Consumer acceptability/Machine learning/Explainability

分类

轻工纺织

引用本文复制引用

Stefano Polimena,Gianvito Pio,Maria Cefola,Michela Palumbo,Michelangelo Ceci,Giovanni Attolico..A novel random forest-based approach for the non-destructive and explainable estimation of ammonia and chlorophyll in fresh-cut rocket leaves[J].Information Processing in Agriculture,2025,12(2):P.221-231,11.

基金项目

supported by the project FAIR-Future AI Research(PE00000013) （PE00000013）

spoke 6–Symbiotic AI,under the NRRP MUR program funded by the NextGenerationEU and by the project Prin 2017“SUS&LOW-Sustaining low-impact practices in horticulture through non-destructive approach to provide more information on fresh produce history and quality”(grant number:201785Z5H9)from the Italian Ministry of University and Research。（grant number:201785Z5H9）

Information Processing in Agriculture

ISSN：2097-0153

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