A Method of Coupling Lucerne Quality with Meteorological Data to Evaluate the Suitability of Hay Harvest

Abstract

The alfalfa harvest time is determined by the alfalfa growth stage and the weather factors at that time, which will affect the yield and quality of the alfalfa hay. Addressing issues like the lack of precise harvesting timing and underutilized production potential of lucerne, this study is based on the internal(fall dormancy level, crude protein, acid, neutral detergent fiber, relative feed value) and external factors(air temperature, precipitation, wind speed, ground temperature, relative humidity, solar radiation) affecting the quality of lucerne, as well as the relevant experimental data of the existing literature and the weather factors within 24 h after the lucerne harvest.Using principal component analysis to calculate the weights of the above indicators, the harvest suitability score formula was constructed to determine the harvesting time, harvesting method and harvesting stubble. Huanghua City was used as an example to confirm the method’s effectiveness in guiding for determining the optimal harvest date of lucerne in the city. Key findings include the following: The hay quality of the first two crops of alfalfa in Huanghua City was higher than that of the third and fourth crops, and the optimal harvest stage of alfalfa was before the precipitation concentration period, which was consistent with other local research results and weather characteristics, and the method was feasible. Precipitation was the most significant factor affecting the lucerne harvest. The effects of other weather factors on hay quality varied with precipitation conditions. The temperature was the second important factor when daily precipitation is less than 1 mm, and the wind speed became the second important factor when the daily precipitation is less than 10 mm and more than 1 mm. Under low suitability and high precipitation, it may be advisable to convert hay harvest to silage to maximize economic benefits. This research could help agricultural decision-makers to develop precise harvesting strategies, and further improve lucerne production efficiency.

Keywords

• lucerne
• evaluate method
• forage management
• meteorological data