Assessment of yield monitoring equipment for dry matter and yield of corn silage and alfalfa/grass

被引:0
|
作者
Emmaline A. Long
Quirine M. Ketterings
David Russell
Francoise Vermeylen
Stephen DeGloria
机构
[1] Cornell University,Nutrient Management Spear Program, Animal Science Department
[2] Cornell University,Nutrient Management Spear Program, Animal Science Department
[3] Agrinetix,Statistical Consulting
[4] LLC,Soil and Crop Sciences Section, School of Integrative Plant Sciences
[5] Cornell University,undefined
[6] Cornell University,undefined
来源
Precision Agriculture | 2016年 / 17卷
关键词
Yield monitor; Self-propelled forage harvester; Alfalfa; Corn silage;
D O I
暂无
中图分类号
学科分类号
摘要
Whole farm evaluations have shown that accurate yield data are difficult to collect for alfalfa (Medicago sativa L.) and grass mixtures and corn (Zea mays L.) silage fields. Additionally, on-farm research, a recommended tool for adaptive management, is hindered by lack of practical ways to collect yield data. Recently, forage yield monitors have become available on self-propelled forage harvesters (SPFHs), but precision and accuracy of this technology are unknown. The objective of this project was to evaluate accuracy of yield and moisture sensing components of forage yield monitors for use in alfalfa/grass and corn silage. Moisture content, mass flow weights, total area harvested and total dry yield per hectare were measured on 11 farms in 2013; forage samples were collected for truck loads, analyzed for dry matter content, and compared to monitor-registered dry matter. Truck weights were used to compare monitor-derived yield to actual yield on two farms for alfalfa/grass and three farms for corn silage. Moisture sensors estimated crop moisture content within 3.7 % DM for alfalfa/grass and 3.0 % DM for corn silage of the oven dry value. Flow sensors estimated alfalfa/grass yield to ±0.5 and ±1.1 Mg DM/ha for corn silage. When calibrations are done regularly, forage yield monitors can provide an accurate and precise measure of dry yield for adaptive management. It is concluded that this technology can be used when plots are large and large treatment-driven yield differences are expected.
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页码:546 / 563
页数:17
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