Are We Up to the Best Practises in Forage and Grassland Precision Harvest? A Review

Abstract

Grassland and forage crops are a domain where the application of precision agriculture techniques has been less intensive so far, compared to grain crops. This is especially evident in the case of variable yield assessment, the step that prompts the adoption of precision management techniques once farmers are faced by unexpectedly high yield spatial variation. Much work has been devoted to forage, grassland and pasture yield assessment since the early 2000's; evaluating the established achievements alongside the existing drawbacks and limitations is seen the best way to lay the foundation for future research work in this field. Self-propelled forage harvesters received most attention in the quest for on-the-go yield assessment. Both volumetric flow (feedroll displacement sensing) and mass flow (impact force and torque sensing) assessments were tested prior to be developed into commercial applications. Nonetheless, their performances vary depending on harvested product characteristics (density, moisture, texture, etc.). Integrating multiple sensor technologies has emerged as the most effective solution to reduce this variability, despite the higher costs involved. Forage handling machines (mowers conditioners, waggon trailers and balers) were also largely addressed. Balers in the static weighing mode are one of the simplest and most reliable yield assessing platforms, although at the expenses of spatial discretization and positional lag of the yield data. Remote sensing based on spectral reflectance data from the standing crop is rapidly gaining interest, especially if performed from satellites. Multiple data sources (e.g., Landsat and MODIS images), sometimes processed through machine learning or neural network techniques, have demonstrated to provide more reliable yield assessments than single data sources. A cross cutting issue in all these techniques is the assessment of forage moisture. At the ground level, near infra-red sensors are gaining popularity over capacitance sensors, thanks to their ability to determine also quality parameters of the harvested biomass. Overall, the need for calibration and maintenance of all sensor types represents a critical point that requires to be carefully evaluated before selecting an appropriate system.