A fruit pick-up mechanism for reducing dust generation in almond pick-up machines
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A fruit pick-up mechanism for reducing dust generation in almond pick-up machines

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Abstract

This doctoral research addresses a critical environmental challenge in California's almond orchards: the pervasive dust pollution stemming from traditional almond harvesting methods. As the leading producer of almonds, supplying over 80 percent of the global demand, California has long been confronted with the adverse effects of these practices on air quality and health, notably the substantial emissions of particulate matter (PM), particularly PM2.5 and PM10.At the core of my study was the conception, design, and iterative development of an innovative low-dust sweeping system aimed at drastically reducing dust emissions during almond harvesting. This journey involved the creation and successive refinement of ten distinct versions of the machine, each iteration addressing limitations and inefficiencies identified in its predecessor. This meticulous process of design and modification was pivotal in evolving the system to its final form, incorporating a sophisticated feedback control mechanism that intelligently adjusts the sweeper brushes’ height and speed in synchrony with the harvester's movement. This innovation significantly refined the interaction between the brushes and the ground, reducing unnecessary sweeping and, as a result, mitigating dust generation. Comparative field tests with conventional harvesting equipment from renowned brands like Flory, Weiss McNair, and Jack Rabbit in Fresno County orchards established that our final low-dust model, encapsulating the refinements from previous versions, notably outperformed its predecessors in minimizing PM emissions. Furthermore, this research made a significant stride in predicting PM2.5 emissions, a previously unaddressed challenge in California's almond industry. The absence of a reliable emission factor for PM2.5 has been a significant barrier to regulatory compliance and emissions inventory. The predictive model developed as part of this research is a substantial contribution toward understanding and managing the environmental impact of almond harvesting operations. In conclusion, the final version of the low-dust almond harvesting system developed through this research not only meets but surpasses California's air quality standards. It offers an effective, environmentally responsible solution for the almond industry, embodying the essence of sustainable innovation and marking a significant step forward in harmonizing agricultural efficiency with environmental stewardship.

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