Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** addressing food waste is crucial…

Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** addressing food waste is crucial for sustainability, especially as the global population grows. From growers to consumers, inefficiencies lead to significant food waste. Consumers prefer visually appealing produce, prompting growers and packers to discard a significant percentage of their product due to misalignment between supply and demand. Efficient models that integrate real-time data can enhance agricultural operations by improving order fulfillment and inventory selection, thereby reducing waste and optimizing harvest, storage, and packing processes.small and medium-sized growers are particularly affected by food loss and waste, which add financial pressure and can deter sustainable farming practices, making growers more vulnerable in the market. Consequently, these growers risk being edged out, reducing the diversity of available produce and increasing centralization in the agriculture sector.to address the GAP between supply and demand, this proposal aims to quantify the impact of inventory management and high-throughput grading technologies on food waste for small- and medium-sized growers selling produce through consignment sellers. The central hypothesis is that improved knowledge of produce grade, both just-in-time and historical, will decrease waste and increase profitability for small- and medium-sized growers. This hypothesis will be tested through three main objectives:1) develop and implement systems to quantify produce waste: install camera systems at nash produce to monitor the pickout and eliminator table belts, producing metrics related to grade, weight, and produce characteristics. This will inform dashboard metrics estimating packout, profitability, revenue, and efficiency.2) develop an online learning system for produce order-inventory matching: update inventory grade distribution to optimize order matching as data becomes available; AND3) create models and methods for defining post-harvest initial conditions: develop a sweetpotato growth model using various degrees of prior knowledge. Validate these models through packing line experiments. The focus will be on sweetpotato as a high-value horticultural crop representative of many graded crops. The results will be broadly applicable to consignment sellers of any graded crops, enhancing sustainability and profitability across the agricultural sector.