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Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches
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| Published in: | Legume Science |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| _version_ | 1868553019520450560 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Legume Science |
| description | |
| discipline_display | Food and Food Industries |
| discipline_facet | Food and Food Industries |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:71771 |
| institution | FRELIP |
| journal_source_facet | Legume Science |
| last_indexed | 2026-06-20T21:30:19.360Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches Food and Food Industries General Food and Food Industries |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Food and Food Industries General Food and Food Industries |
| subject_facet | Food and Food Industries General Food and Food Industries |
| title | Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches |
| title_alt | Evaluación de calidad y modelado predictivo del rendimiento de garbanzo, lenteja y camelina: efectos de nitrógeno, riego, condiciones de secano e intercultivo usando enfoques de aprendizaje automático Évaluation de la qualité et modélisation prédictive du rendement du pois chiche, de la lentille et de la caméline : effets de l'azote, de l'irrigation, des conditions pluviales et de la culture intercalaire à l'aide d'approches d'apprentissage automatique Avaliação da qualidade e modelagem preditiva do rendimento de grão-de-bico, lentilha e camelina: efeitos de nitrogênio, irrigação, condições de sequeiro e consórcio usando abordagens de aprendizado de máquina |
| title_auth | Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches |
| title_es_txt | Evaluación de calidad y modelado predictivo del rendimiento de garbanzo, lenteja y camelina: efectos de nitrógeno, riego, condiciones de secano e intercultivo usando enfoques de aprendizaje automático |
| title_fr_txt | Évaluation de la qualité et modélisation prédictive du rendement du pois chiche, de la lentille et de la caméline : effets de l'azote, de l'irrigation, des conditions pluviales et de la culture intercalaire à l'aide d'approches d'apprentissage automatique |
| title_full | Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches |
| title_fullStr | Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches |
| title_full_unstemmed | Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches |
| title_pt_txt | Avaliação da qualidade e modelagem preditiva do rendimento de grão-de-bico, lentilha e camelina: efeitos de nitrogênio, irrigação, condições de sequeiro e consórcio usando abordagens de aprendizado de máquina |
| title_short | Quality Assessment and Predictive Modeling of Chickpea, Lentil and Camelina Yield: Effects of Nitrogen, Irrigation, Rainfed Conditions, and Intercropping Using Machine Learning Approaches |
| title_sort | quality assessment and predictive modeling of chickpea, lentil and camelina yield: effects of nitrogen, irrigation, rainfed conditions, and intercropping using machine learning approaches |
| topic | Food and Food Industries General Food and Food Industries |
| url | https://onlinelibrary.wiley.com/doi/10.1002/leg3.70091?af=R |