{"id":186482,"date":"2025-05-05T10:21:48","date_gmt":"2025-05-05T14:21:48","guid":{"rendered":"https:\/\/www.hajim.rochester.edu\/senior-design-day\/?p=186482"},"modified":"2026-05-04T09:42:35","modified_gmt":"2026-05-04T13:42:35","slug":"zalliant-integrating-forecasting-for-weather-optimized-crop-cutting","status":"publish","type":"post","link":"https:\/\/www.hajim.rochester.edu\/senior-design-day\/zalliant-integrating-forecasting-for-weather-optimized-crop-cutting\/","title":{"rendered":"Zalliant: Integrating Forecasting for Weather-Optimized Crop Cutting"},"content":{"rendered":"\n<p class=\"has-text-align-left\"><strong>Team members:<\/strong> Skye Crocker, Colin Hascup, Ahmed Malik, Lam Nguyen, Ruilin Zhang<br><strong>Sponsor<\/strong>: Zalliant | <strong>Instructors<\/strong>: Ajay Anand, Ph.D. Cantay Caliskan, Ph.D.<\/p>\n\n\n\n<p class=\"has-text-align-left\">Drying crops before storage as hay or silage is critical for preserving quality, with environmental drying being the preferred method due to its cost-effectiveness. This project, conducted in collaboration with Zalliant, aimed to develop predictive models to optimize crop harvesting and drying decisions based on weather conditions.<\/p>\n\n\n\n<p>The project involved two key models:<\/p>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li><strong>Growing Degree Day (GDD) Calculator<\/strong>: This tool estimates crop maturity by calculating cumulative heat values, helping farmers determine the ideal harvest window. For example, alfalfa is typically harvested at 750\u2013755 GDD. The calculator supports multiple calculation methods (e.g., average, sine, triangle) and customizable temperature thresholds. Validation using USDA harvest reports confirmed alignment between predicted and actual harvest dates.<\/li>\n\n\n\n<li><strong>Drying Calculation Algorithm<\/strong>: Using a formula derived from agronomic research, this model predicts moisture content over time post-harvest. It assists farmers in deciding when to switch from field drying to mechanical drying. While validation data were limited, the algorithm\u2019s foundation in established literature and adaptability to hourly weather data ensures its potential utility.<\/li>\n<\/ol>\n\n\n\n<p>Key innovations include a flexible GDD calculator generalizable across U.S. locations, capable of using multiple calculation methods and custom temperature settings. To further optimize harvest dates, we recommend enhancing data collection, including moisture content and harvest timing. Future work involves expanding the models to other crops, refining granularity with hourly data, and validating results through live testing. This project set up a foundation for future work on optimizing the cutting and drying of crops. Zalliant now has a more integrated pathway for GDD and drying calculations. <\/p>\n\n\n\n<p><strong>Reference<\/strong><\/p>\n\n\n\n<p><a href=\"https:\/\/www.researchgate.net\/publication\/269990251_Alfalfa_Drying_Model_for_the_Field_Environment\">Rotz, C.A. &amp; Chen, Yi. (1985). Alfalfa Drying Model for the Field Environment. Transactions of the ASAE. American Society of Agricultural Engineers. 28. 1687-1672. 10.13031\/2013.32500.<\/a><br><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/www.hajim.rochester.edu\/senior-design-day\/wp-content\/uploads\/2025\/04\/DSCC483_Final_Poster-1.pdf\" type=\"application\/pdf\" style=\"width:100%;height:680px\" aria-label=\"PDF embed\"><\/object><a href=\"https:\/\/www.hajim.rochester.edu\/senior-design-day\/wp-content\/uploads\/2025\/04\/DSCC483_Final_Poster-1.pdf\" class=\"wp-block-file__button wp-element-button\" download>Download<\/a><\/div>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Team members: Skye Crocker, Colin Hascup, Ahmed Malik, Lam Nguyen, Ruilin ZhangSponsor: Zalliant | Instructors: Ajay Anand, Ph.D. Cantay Caliskan, Ph.D. Drying crops before storage as hay or silage is&hellip;<\/p>\n","protected":false},"author":15492,"featured_media":193682,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[4442,106],"tags":[16522],"coauthors":[20082,20092,20022,20102,20112],"class_list":["post-186482","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-archive","category-dsc-archive","tag-data-science"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Zalliant: Integrating Forecasting for Weather-Optimized Crop Cutting - Senior Design Day<\/title>\n<meta name=\"description\" content=\"Zalliant seeks to optimize crop harvesting and drying decisions through weather-based forecasting. To deliver against this goal, the team developed two models: 1) a Growing Degree Day (GDD) calculator that determines ideal harvest timing by tracking cumulative heat values (e.g., alfalfa at 750\u2013755 GDD), validated against USDA reports, and 2) a drying algorithm that predicts post-harvest moisture decay to guide mechanical drying transitions. While validation data were limited, the algorithm\u2019s foundation in established literature and adaptability to hourly weather data ensures its potential utility. While further validation is planned, these models establish a robust foundation for Zalliant to reduce drying costs and improve crop storage outcomes. Future enhancements will expand crop coverage and incorporate hourly weather data for greater precision.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.hajim.rochester.edu\/senior-design-day\/zalliant-integrating-forecasting-for-weather-optimized-crop-cutting\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Zalliant: Integrating Forecasting for Weather-Optimized Crop Cutting - Senior Design Day\" \/>\n<meta property=\"og:description\" content=\"Zalliant seeks to optimize crop harvesting and drying decisions through weather-based forecasting. To deliver against this goal, the team developed two models: 1) a Growing Degree Day (GDD) calculator that determines ideal harvest timing by tracking cumulative heat values (e.g., alfalfa at 750\u2013755 GDD), validated against USDA reports, and 2) a drying algorithm that predicts post-harvest moisture decay to guide mechanical drying transitions. While validation data were limited, the algorithm\u2019s foundation in established literature and adaptability to hourly weather data ensures its potential utility. While further validation is planned, these models establish a robust foundation for Zalliant to reduce drying costs and improve crop storage outcomes. Future enhancements will expand crop coverage and incorporate hourly weather data for greater precision.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.hajim.rochester.edu\/senior-design-day\/zalliant-integrating-forecasting-for-weather-optimized-crop-cutting\/\" \/>\n<meta property=\"og:site_name\" content=\"Senior Design Day\" \/>\n<meta property=\"article:published_time\" content=\"2025-05-05T14:21:48+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-05-04T13:42:35+00:00\" \/>\n<meta name=\"author\" content=\"Skye Crocker (UG), Colin Hascup (UG), Lam Nguyen (UG), Ahmed Malik (G), Ruilin Zhang\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Skye Crocker (UG), Colin Hascup (UG), Lam Nguyen (UG), Ahmed Malik (G), Ruilin Zhang\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.hajim.rochester.edu\\\/senior-design-day\\\/zalliant-integrating-forecasting-for-weather-optimized-crop-cutting\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.hajim.rochester.edu\\\/senior-design-day\\\/zalliant-integrating-forecasting-for-weather-optimized-crop-cutting\\\/\"},\"author\":{\"name\":\"Skye Crocker (UG)\",\"@id\":\"https:\\\/\\\/www.hajim.rochester.edu\\\/senior-design-day\\\/#\\\/schema\\\/person\\\/69348570fb9df559cc96cc5c964907ef\"},\"headline\":\"Zalliant: Integrating Forecasting for Weather-Optimized Crop Cutting\",\"datePublished\":\"2025-05-05T14:21:48+00:00\",\"dateModified\":\"2026-05-04T13:42:35+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.hajim.rochester.edu\\\/senior-design-day\\\/zalliant-integrating-forecasting-for-weather-optimized-crop-cutting\\\/\"},\"wordCount\":307,\"image\":{\"@id\":\"https:\\\/\\\/www.hajim.rochester.edu\\\/senior-design-day\\\/zalliant-integrating-forecasting-for-weather-optimized-crop-cutting\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.hajim.rochester.edu\\\/senior-design-day\\\/wp-content\\\/uploads\\\/2025\\\/04\\\/DSCC483_Final_Poster-2-pdf.jpg\",\"keywords\":[\"Data Science\"],\"articleSection\":[\"3. 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