Predicting how much biochar you’ll get—and what it’s made of—can be tricky, especially when your data isn’t perfect. This Texas A&M study tackles that problem with a smart deep learning model that uses a ResNet-based autoencoder. It’s built to handle missing or messy data, and it still makes solid predictions about biochar yield and content. Compared to other models like Random Forest and XGBoost, this one holds up better under uncertainty, making it a helpful tool for anyone working to fine-tune biochar production.
When dairy farms face sudden disruptions—like plant shutdowns or weather emergencies—disposing of surplus milk becomes a serious challenge. This study from Texas A&M explores three practical on-farm solutions: lagoon discharge, composting, and land application. Each method has pros and cons. Lagoons can handle large volumes but risk overload; composting improves compost quality if managed well; and land application can support soil and crop health, though it must be done carefully. Splitting milk into smaller, repeated applications helped reduce environmental impact across all methods. These insights offer farmers practical guidance during unexpected milk disposal events.
Monitoring lagoon water doesn’t have to rely on expensive lab equipment—this study proposes using photos and machine learning instead. Researchers from Texas A&M captured images of lagoon water and used RGB color data to estimate levels of nitrogen, phosphorus, solids, and bacteria. They trained machine learning models that predicted water quality with high accuracy, especially using the blue color channel. The findings show promise for developing simple, low-cost tools—like smartphone apps—that can help farmers keep an eye on lagoon health in real time.
This Texas A&M pilot study explores the use of virtual reality (VR) videos as an innovative tool for extension education on manure and mortality management. The research shows that VR videos significantly increase participants’ awareness, especially among less-experienced users. By offering immersive, hazard-free learning experiences, VR eliminates the need for in-person site visits. Participants rated the videos as engaging and effective, suggesting that VR could enhance outreach efforts and modernize agricultural extension training.