Improving the Conversion Efficiency of Photosynthetically Active Radiation (PAR) Absorbed by Winter Wheat Under Deficit Irrigation Using Cost-Effective Autonomous IoT Devices
Notice bibliographique
Résumé
Water shortage is considered the most critical issue in the regions of arid and semi-arid climate, which is affecting the growth cycle and yield of the winter wheat crop (Triticum durum Desf.). Consequently, irrigation is necessary to increase crop production and maximize water use efficiency (WUE). This study was carried out over three consecutive cropping seasons (2021-2022), (2022-2023), and (2023-2024) at the Research Unit of the National Institute of Rural Engineers, Water and Forests (INRGREF) at Cherfech. This study was aimed at examining the impact of three levels of continued deficit irrigation (D1 = 75% ETc, D2 = 60% ETc, and D3 = not irrigated only by rainfall) on leaf area index (LAI), water consumption (WC), photosynthetic active radiation absorbed (PARabs), radiation use efficiency of grain yields (RUEY), and the relationship between cumulative WC and cumulative PARabs. The cost-effective and precise autonomous Internet of Things device with artificial intelligence at the edge was utilized to monitor irrigation and crop water consumption. At harvest, a decrease in TPDM was registered in the two treatments, DI2 and DI3, by (30.2%; 29%) and (40%; 38.7%) in 2020-2021, (14.7%; 12.3%) and (32%; 30.1%) in 2022-2023, and (19.7%; 14%) and (38%; 34.1%) in 2023-2024, when contrasted with the respective DI1 and FI treatments, respectively. During the three-cropping season (2021-2024), ANOVA analysis revealed that DI and FI treatments were not significantly affected (P ˃ 0.05) by the accumulated PARabs. The cumulative PARabs in D2 and D3 were dropped to 1.7% and 4.9%, respectively, compared to FI. In the second season (2022-2023) and in the third season (2023-2024), the PARabs in D2 and D3 decreased by (4 - 4.9%) and (15.7 - 15.8%), respectively, compared with FI. The lowest GY was registered under a rainfed treatment, and it decreased from 64.5 to 68.6% in the three experiments compared to FI. The highest RUEY was registered in FI. There was a reduction in D1 and D2 in the first season of 6.6% and 51.9%, respectively, compared with FI. Under the treatment D2 at the second and third seasons, the RUEY decreased from 28.6 to 43% compared to the control treatment. Photosynthetically active radiation (PARabs) and crop water consumption (CWC) have a strong linear relationship; this relationship can be used to estimate crop water requirements as a simple measure of cumulative radiation absorbed (cereal crops).
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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