Integration of summer and fall cover crops in vegetable cropping systems
Notice bibliographique
Résumé
The demand for locally produced vegetables is growing in the Midwest, including Iowa. However, since vegetables are a small fraction of total cropland in the state, little research exists on approaches and techniques to increase the sustainability of vegetable production systems. Including cover crops in vegetable crop rotations can contribute to sustainability in vegetable cropping systems. This research investigated the integration of summer and fall cover crops in vegetable cropping systems to reduce weeds and nutrient leaching, improve soil chemical and biological properties, and enhance crop growth, yield, and produce quality. Cover crops studied in this research included buckwheat (Fagopyrum esculentum), cereal rye (Secale cereal), cowpea (Vigna unguiculata), crimson clover (Trifolium incarnatum), oats (Avena strigosa), oilseed radish (Raphanus sativus var. oleifera), and sorghum-sudangrass (Sorghum bicolor ssp. drummondii). Effects of these cover crops were tested on fall production of cabbage (Brassica oleracea ‘Caraflex’) and lettuce (Lactuca sativa ‘Adriana’) and spring production of potato (Solanum tuberosum ‘Yukon Gold’ and ‘Red Pontiac’).\nIn vegetable cropping systems, weeds have been traditionally managed through tillage or chemicals. With growing awareness and demand for sustainably grown produce, growers are interested in using weed control strategies that could provide environmental benefits. Two of the studies conducted as part of this research investigated effects of four cover crops (buckwheat, cowpea, oats, and sorghum-sudangrass) on fall cabbage and lettuce production. Both studies were a split-plot randomized complete block design with cover crops as the whole plot and planting date of the vegetable as the subplot factor. Two planting dates were tested (immediately after or eight days after cover crop soil incorporation). The third study investigated the effect of fall planted cover crops (cereal rye, crimson clover, and oilseed radish) on soil nutrient concentrations, weed populations and growth, yield and quality of the successive spring potato crop. The study was a Latin square split-plot design with cover crop as the whole plot and potato cultivars as the subplot factor. All three studies included a no cover crop plot as a control treatment.\nThe first two studies clearly showed that cover crops can be used to help manage weeds during the summer time before planting of a fall vegetable crop. Cover crop biomass was highest for sorghum-sudangrass. Cowpea cover crop produced the lowest biomass. Buckwheat was the best cover crop at suppressing weeds while cowpea did not sufficient weed suppression. All cover crops did suppress weeds compared to the control. In the cabbage study, cowpea had a positive effect on soil nitrate concentration and produced the highest marketable cabbage yields (10,654 and 7,838 kg.ha-1 in 2013 and 2014, respectively). There was trending evidence that the sorghum-sudangrass cover crop detrimentally affected the growth and yield of the cabbage crop. Between the two planting times, early planting (immediately after cover crop soil incorporation) seemed to benefit cabbage yield only in the cowpea treatment. Results in the lettuce study were very similar. Cowpea shortened the time to harvest for the lettuce crop. The decrease in days to maturity was a minimum of 5 d in 2013 to 13 d in 2014. The early planting also showed evidence in decreasing the days to maturity. In 2014 planting immediately after soil incorporation of buckwheat and the control treatments, decreased the days to maturity of the lettuce crop than those planted eight days after soil incorporation of the buckwheat and control treatments.\nThe third study with fall planted cover crops, examined how cover crops influenced soil nitrogen, weeds and yield of the following potato crop. Positive effects were seen from the cover crops on increasing soil nitrogen and decreasing weed populations but, the advantages were short lived. These advantages did not result in a crop yield increase or decrease in the following potato crop. All three experiments demonstrate that cover crops can be incorporated into vegetable production systems on Iowa’s landscape to provide environmental benefit without negatively affecting yield.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».