Most models focus on either crop recommendation or yield

The gap

Evidence profile

Stated in the cells research gap and abstract sections of the source papers, classified as general, drawn from work published between 2021 and 2026, spanning 5 journals. Those papers have been cited 47 times in total.

Supporting evidence — 5 representative gaps

• Phenology-based learning framework for yield estimation and harvest forecasting of raspberry fruits (2026) · International Journal of Intelligent Robotics and Applications · doi

  Yield prediction and harvest time estimation remain practical challenges for farmers. - Phenological tracking remains largely manual, prone to error, and difficult to scale.

  generalstated in cells research gapevidence 5/5
  Keywords: yield prediction harvest time estimation remain practical challenges
• A Soil-Aware Hybrid AI Model for Precision Crop Recommendation and Yield Forecasting (2026) · Engineering, Technology & Applied Science Research · doi

  Existing research addresses either crop recommendation or yield prediction, but not both. - There is a need for modern decision support systems to provide estimated Crop Yield (CY) and ensure that output meets market requirements.

  generalstated in cells research gapevidence 5/5
  Keywords: existing research addresses either crop recommendation yield prediction
• Smart Agriculture: Leveraging Machine Learning for Crop Recommendation, Fertilizer Optimization, and Yield Prediction (2026) · International Journal of Intelligent Systems and Applications · doi

  Most models focus on either crop recommendation or yield prediction in isolation. - Few systems integrate crop, fertilizer, and yield prediction into a single tool.

  generalstated in cells research gapevidence 5/5
  Keywords: models focus either crop recommendation yield prediction isolation
• Crop Yield Prediction and Disease Detection (2026) · International Journal for Research in Applied Science and Engineering Technology · doi

  Existing systems lack an integrated approach for disease detection and yield prediction. - Traditional statistical methods are often insufficient for crop yield prediction.

  generalstated in cells research gapevidence 5/5
  Keywords: existing systems lack integrated approach disease detection yield
• How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia (2021) · Food Policy · cited 47× · doi

  However, in practice, crop cuts and other sample-based protocols vary widely in the details of their implementations and little empirical work has documented how alternative yield estimation methods perform.

  generalstated in abstractevidence 4/5
  Keywords: practice crop cuts sample based protocols vary widely details implementations little empirical documented alternative yield

Questions about this gap