Robotic agricultural instrument for automated extraction of nematode cysts and eggs from soil to improve integrated pest management

Author:

Legner Christopher M.,Tylka Gregory L.,Pandey Santosh

Abstract

AbstractSoybeans are an important crop for global food security. Every year, soybean yields are reduced by numerous soybean diseases, particularly the soybean cyst nematode (SCN). It is difficult to visually identify the presence of SCN in the field, let alone its population densities or numbers, as there are no obvious aboveground disease symptoms. The only definitive way to assess SCN population densities is to directly extract the SCN cysts from soil and then extract the eggs from cysts and count them. Extraction is typically conducted in commercial soil analysis laboratories and university plant diagnostic clinics and involves repeated steps of sieving, washing, collecting, grinding, and cleaning. Here we present a robotic instrument to reproduce and automate the functions of the conventional methods to extract nematode cysts from soil and subsequently extract eggs from the recovered nematode cysts. We incorporated mechanisms to actuate the stage system, manipulate positions of individual sieves using the gripper, recover cysts and cyst-sized objects from soil suspended in water, and grind the cysts to release their eggs. All system functions are controlled and operated by a touchscreen interface software. The performance of the robotic instrument is evaluated using soil samples infested with SCN from two farms at different locations and results were comparable to the conventional technique. Our new technology brings the benefits of automation to SCN soil diagnostics, a step towards long-term integrated pest management of this serious soybean pest.

Funder

National Science Foundation

U.S. Department of Agriculture

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference63 articles.

1. USDA. Economic Research Service: Soybeans & Soil Crops (2020). https://www.ers.usda.gov/topics/crops/soybeans-oil-crops/. Accessed 15 October 2020.

2. USDA. Foreign Agricultural Service: Soybeans (2019). https://www.fas.usda.gov/commodities/soybeans. Accessed 15 October 2020.

3. United Soybean Board. Soy Demand is Growing All Over (2019). https://www.unitedsoybean.org/article/soy-demand-is-growing-all-over. Accessed 15 October 2020.

4. Soybean Meal Info Center. World soybean production. INFO Source Newsl. (2018). https://www.soymeal.org/soy-meal-articles/world-soybean-production/. Accessed 15 October 2020.

5. American Soybean Association. 2017 Soy Stats A Reference Guide to Important Soybean Facts and Figures (2017). https://www.agri-pulse.com/ext/resources/AgSummit/2017-SoyStats.pdf.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3