Background: Oat (Avena sativa L.) is a valuable crop due to its strong adaptability to marginal environments, making it an important component of agricultural systems in regions where other cereals may not thrive. The application of chemical fertilizer can influence oat hay and grain yield significantly. However, large-scale meta-analytical studies of the size and variability of oat hay and grain yields in response to fertilizer addition are still lacking. Based on 83 studies worldwide, this meta-analysis quantifies the impact of the addition of fertilizer on oat hay and grain yields under varying environmental conditions (e.g., soil nutrient levels, texture, and climate).
Results: The results confirmed that the fertilizer application increased oat hay yield by 48.9% and grain yield by 36.2%. This study demonstrated that balanced fertilization with nitrogen, phosphorus, and potassium generally enhances oat hay and grain yield despite large temporal and spatial variations. Boosted regression tree (BRT) models suggest that changes in hay and grain yield were primarily dominated by soil pH and nitrogen fertilizer. The response ratio (the natural logarithm of the mean values of hay yield or grain yield with and without fertilization, respectively) of hay yield declined linearly with soil pH. Elevation was the second most important factor affecting the change in response ratio of hay yield and the third most important factor affecting the change in response ratio of grain yield but climatic conditions were not the dominant factors affecting changes in oat hay or grain yield.
Conclusion: Overall, these results will benefit producers considering site-specific fertilization management of oat. They could increase yields and save investment in fertilizer, and help to facilitate the genetic breeding of oat varieties with high nutrient use efficiency. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Keywords: altitude; boosted regression tree; environmental factor; managerial factors; meta‐analysis; soil pH.
© 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.