Organic agriculture enhances zinc concentrations in edible crop parts: A meta-analysis
Notice bibliographique
Résumé
Zinc (Zn) and iron (Fe) are essential micronutrients for humans, and their deficiencies lead to widespread malnutrition and other related health problems. Organic agriculture is often promoted for its potential to enhance soil health and environmental sustainability, but its effects on Zn and Fe concentrations in crops have remained inconsistent. This meta-analysis aimed to compare Zn and Fe concentrations, and also evaluated crop yield, between organic and conventional agriculture systems. It also sought to identify environmental and agronomic factors that influence these outcomes. A total of 322 paired data points from 54 peer-reviewed publications on cereals, legumes, and vegetables were analyzed. The natural logarithm of the response ratio (lnRR) was employed as the effect size for Zn and Fe concentrations in edible crop parts and crop yield. The influences of crop type, soil properties (soil texture, soil organic carbon, soil pH) and climate factors (climate region, annual mean air temperature, annual precipitation) on the effect sizes were assessed using a mixed-effects model. Zinc concentrations in organically grown crops were 14.2 % (95 % CI: 9.7 – 19.0 %, p < 0.001) higher than those under conventional agriculture, with the effectiveness being more evident in vegetables. This increase corresponded to an average of 4.3 mg kg -1 higher Zn concentrations across crop types. Iron concentrations did not show an overall difference between the two systems, only under wet conditions (annual precipitation > 850 mm) where organically grown crops had 14.5 % (95 % CI: 3.57 – 26.66 %, p < 0.001) higher Fe concentration than conventionally grown crops. Despite these effects on micronutrients, organic agriculture was associated with a 24.7 % (95 % CI: −31.2 to −17.6 %, p < 0.001) reduction in crop yield, especially for cereals grown in arid regions. These findings underscore a critical trade-off between nutritional micronutrient concentration and crop productivity. This is the first meta-analysis comparing organic and conventional agriculture regarding their impacts on micronutrient availability in crops. The findings highlight the need for integrated agronomic strategies that optimize nutrient quality while maintaining productivity. Bioavailability was not assessed in the present study but is highlighted as an urgent research priority when examining how organic systems influence micronutrient bioavailability for human consumption. • Organic farming increases Zn in crops by 14.2 %, especially in vegetables. • No overall significant difference in Fe was observed between farming systems. • Organic systems show 24.7 % lower yield, mainly for cereals from arid regions. • Trade-off exists between micronutrient gain and yield loss in organic farming.
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Comment cette classification a été obtenuedéplier
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,004 |
| Études des sciences et des technologies | 0,000 | 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) | 0,002 | 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».