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Technologies for Enhancing Pecan Production and Processing

机译：促进山核桃生产和加工的技术

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This paper summarizes research at Oklahoma State University (OSU) to develop innovative technologies that provide solutions to issues and problems affecting pecan production and processing. Some of the projects areas include;1. Pecan yield estimation technique using backscattered terrestrial microwave sensing.2. Dielectric spectroscopy for estimating quality of in-shell pecans.3. Wireless image sensor networks in estimating the population of pecan weevils.4. Low-cost small-scale sanitizer for in-shell pecans.5. Optical sensors and algorithms that adequately predict plant N status for nitrogen management.6. X-ray machine vision inspection systems for pecan defect identification.Accurate estimates of pecans in the field prior to harvest are critically important for production management decisions and marketing. Pecan producers, processors and marketers identified improved accuracy of crop estimates as a research priority for theindustry. The pecan weevil (Curculio caryae) is considered a key pest. Without timely insecticide treatments, crop losses can exceed 75%. Research has focused on the design of a wireless sensor network for real-time monitoring and population estimationof pecan weevils. Nitrogen (N) has become a major cost in producing pecans. Traditionally, N is applied once or twice per season. Application rates usually exceed the minimum N requirement for optimum production. Research has focused on reducing N inputswhile maintaining production levels. Sorting of defective nuts is difficult because nutmeat defects are not fully recognizable by physical properties, color and appearance of whole unshelled nuts. Commercial sorters are available to sort nutmeat after shelling the nuts, but this results in unnecessary shelling of defective nuts. Development of automated inspection systems to identify good pecan nuts from defective ones before shelling would reduce processing costs. Due to space limitations, only the highlights of each research area will be presented. Interested readers desiring more comprehensive discussion of the projects are encouraged to access the references.
机译：本文总结了俄克拉何马州立大学（OSU）开发创新技术的研究，这些技术可为影响山核桃生产和加工的问题提供解决方案。一些项目领域包括：1。利用反向散射地面微波感测的山核桃产量估算技术2。介电光谱法用于评估带壳山核桃的质量3。无线图像传感器网络估计山核桃象鼻虫的数量。4。适用于带壳山核桃的低成本小型消毒剂5。光学传感器和算法可充分预测植物的氮素状态以进行氮管理6。用于识别山核桃缺陷的X射线机器视觉检查系统。收获前在田间对山核桃进行准确估算对于生产管理决策和市场营销至关重要。美国山核桃的生产者，加工者和销售者认为，提高作物估计的准确性是该行业的研究重点。山核桃象鼻虫（Curculio caryae）被认为是主要害虫。没有及时的杀虫剂处理，农作物损失可能超过75％。研究集中在无线传感器网络的设计上，以实时监测和评估胡桃象鼻虫。氮已成为生产山核桃的主要成本。传统上，每季施用N一次或两次。施用量通常超过最佳生产所需的最低氮含量。研究集中在减少氮的投入，同时保持产量水平。有缺陷的坚果很难分类，因为不能通过物理特性，颜色和整个带壳坚果的外观完全识别出坚果的缺陷。剥壳后可使用商用分拣机对坚果进行分拣，但这会导致不必要的脱壳有缺陷的坚果。开发自动检查系统以在脱壳之前从有缺陷的山核桃中识别出好的山核桃将减少加工成本。由于篇幅所限，仅介绍每个研究领域的重点。希望对项目进行更全面讨论的感兴趣的读者可以阅读参考文献。

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