我们是否达到了牧草和草地精确收获的最佳实践?回顾

IF 2.7 3区 农林科学 Q1 AGRONOMY
Roberta Martelli, Abid Ali, Valda Rondelli, Lorenzo Barbanti
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引用次数: 0

摘要

与粮食作物相比,草地和饲料作物是迄今为止精准农业技术应用较少的领域。这在可变产量评估的情况下尤为明显,一旦农民面临意外的高产量空间变化,这一步骤就会促使采用精确管理技术。自2000年代初以来,牧草、草地和牧草产量评估工作已投入大量工作;评估现有的成就以及现有的缺陷和局限性被认为是为该领域未来的研究工作奠定基础的最好方法。自走式饲草收割机在进行产量评估方面受到了最多的关注。体积流量(馈辊位移传感)和质量流量(冲击力和扭矩传感)评估在开发到商业应用之前都进行了测试。尽管如此,它们的性能取决于收获的产品特性(密度、湿度、质地等)。尽管成本较高,但集成多种传感器技术已成为减少这种可变性的最有效解决方案。饲草处理机器(割草机,货车拖车和打包机)也主要解决。静态称重模式的打包机是最简单、最可靠的产量评估平台之一,但代价是产量数据的空间离散化和位置滞后。基于直立作物光谱反射率数据的遥感正迅速引起人们的兴趣,特别是通过卫星进行的遥感。多个数据源(例如Landsat和MODIS图像),有时通过机器学习或神经网络技术进行处理,已被证明比单一数据源提供更可靠的产量评估。所有这些技术中的一个交叉问题是牧草水分的评估。在地面上,近红外传感器比电容传感器更受欢迎,因为它们能够确定收获的生物质的质量参数。总的来说,对所有传感器类型的校准和维护的需求是一个关键点,在选择合适的系统之前需要仔细评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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.

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来源期刊
Grass and Forage Science
Grass and Forage Science 农林科学-农艺学
CiteScore
5.10
自引率
8.30%
发文量
37
审稿时长
12 months
期刊介绍: Grass and Forage Science is a major English language journal that publishes the results of research and development in all aspects of grass and forage production, management and utilization; reviews of the state of knowledge on relevant topics; and book reviews. Authors are also invited to submit papers on non-agricultural aspects of grassland management such as recreational and amenity use and the environmental implications of all grassland systems. The Journal considers papers from all climatic zones.
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