Water and nitrogen use efficiency of corn (Zea mays L.) under water table management
Notice bibliographique
Résumé
Drainage and water table management are essential for crop production in humid regions. Water table management not only increases crop yield, but also reduces nitrate leaching to water bodies. This study investigated the water and nitrogen use efficiency of corn under two water management conditions and three nitrogen fertilizer levels. The sap flow heat balance method was used to measure the daily water uptake of corn, over an extended period of the growing season. The impacts of climate change on grain corn and biomass yield in eastern Canada under tile drained conditions was also evaluated over a 30 year future period (2040 to 2069). The study was conducted at a field scale in 2008 and 2009 at St. Emmanuel, Quebec. The two water management conditions were: conventional drainage (FD), and controlled drainage with subirrigation (CD-SI). The three nitrogen (N) fertilizer treatments (low, medium, and high N) were applied in a strip across three blocks. The seasonal water balance indicated that the plants in the CD-SI plots had more water than required in the wet periods, despite the system automation, while the FD plots exhibited deficit water conditions. Water could be saved in the wet periods by better regulating water supplied by subirrigation. However, in dry years, the CD-SI system increased yield. The grain corn water use efficiency (WUE) for FD plots was 2.49 and 2.46 kg m-3, in 2008 and 2009, respectively. In these years, the grain WUE for CD-SI plots was 2.43 and 2.26 kg m-3. Water management treatments demonstrated significant difference (p < 0.05) in grain yields in 2009, at low and high nitrogen levels. However, at the medium nitrogen level, water management demonstrated no significant effect (p > 0.05) on grain yields. The two water treatments had no effect on the above-ground dry biomass yields in both years. Mean nitrogen use efficiency (NUE) of grain corn and biomass varied from 27 to 99 kg kg-1. Highest NUE (99 kg kg-1) was observed under low N (~120 kg N ha-1) and lowest NUE (41 kg kg-1) occurred in the high N (~260 kg N ha-1). This might be due to higher nitrogen losses due to leaching, residual nitrogen in the soil, and more denitrification in high N plots. The rate of plant water uptake measured by the sap flow method, varied from 3.55 to 5.11 mm d-1 from silking to full dent stage of corn growth. These rates were consistent with ETc calculated by the FAO-56 Penman-Monteith method (3.70 to 5.93 mm d-1) for both years. Although, silking is considered as a critical stage for corn growth, water demand was highest at the milk stage (45.63 to 59.80 mm). Transpiration during this stage constituted 10 to12% of the total water requirement of the corn for the season. The silking to full dent stage accounted for approximately 40% of the total water requirement of the crop. The STICS (JavaStics v1.0) crop model was used to examine the impacts of climate change, under the B1 emissions scenario, on corn yield from 2040-2069. The model was calibrated using 2008 field measured data, and then validated using the 2009 data set. Corn grain yield was underestimated by 1.5 to 2.6 Mg ha-1 for the two years of measurement. Total dry biomass was also underestimated by 0.9 to 2.6 Mg ha-1. Simulations for the B1 emissions scenario using synthetic weather data was run under the same crop conditions as in 2008. Tukey's studentized range (HSD) test of corn grain yield indicated that yields at high and low N, and high and medium N were different at the 95% confidence level. Grain and biomass production from 2040-2069 under B1 emissions scenario responded differently (p < 0.05) for the three N treatments. However, the Mann–Kendall test showed neither increasing nor decreasing trend (MK-stat > - 1.96) at a 95% confidence level.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 source (Gemma direct ou Codex distillé), 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 ».