{"id":57,"date":"2026-06-22T09:58:08","date_gmt":"2026-06-22T09:58:08","guid":{"rendered":"https:\/\/veloxintelligence.dev\/index.php\/case-study\/crop-disease-detection-app-for-field-agronomists\/"},"modified":"2026-06-22T09:58:08","modified_gmt":"2026-06-22T09:58:08","slug":"crop-disease-detection-app-for-field-agronomists","status":"publish","type":"velox_case","link":"https:\/\/veloxintelligence.dev\/index.php\/case-study\/crop-disease-detection-app-for-field-agronomists\/","title":{"rendered":"Crop Disease Detection App for Field Agronomists"},"content":{"rendered":"<p>Field agronomists were spending hours identifying crop diseases. We built a Flutter app running a TensorFlow Lite model on-device \u2014 point the phone at a plant and get an instant diagnosis. Works fully offline.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Field agronomists were spending hours identifying crop diseases. 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