agriculture7 papersavg year 2025moderate evidence

Conventional agricultural methods are subjective

Research gap analysis derived from 7 agriculture papers in our local library.

The gap

Conventional agricultural methods are subjective and do not maximize crop choice. There is a need for an intelligent crop recommendation system.

Evidence profile

Sourced from the stated research gap and abstract of the source papers, classified as general, drawn from work published between 2021 and 2026, spanning 6 journals. Those papers have been cited 47 times in total.

Research trend

Established — well-defined area with open sub-problems.

Supporting evidence — 7 representative gaps

  • Intelligent Crop Recommendation System Using Machine Learning (2026) · International Journal for Research in Applied Science and Engineering Technology · doi

    Conventional agricultural methods are subjective and do not maximize crop choice. There is a need for an intelligent crop recommendation system.

    generalstated research gap
    Keywords: conventional agricultural methods subjective maximize crop choice there
  • 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 research gapevidence 5/5
    Keywords: yield prediction harvest time estimation remain practical challenges
  • CY-Bench: a comprehensive benchmark dataset for sub-national crop yield forecasting (2026) · Earth System Science Data · doi

    Prior research for in-season, pre-harvest crop yield forecasting has primarily been case-study based, making it difficult to compare modeling approaches and measure progress systematically.

    generalstated research gapevidence 5/5
    Keywords: prior research in-season pre-harvest crop yield forecasting has
  • 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 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 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 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.

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

Questions about this gap

Conventional agricultural methods are subjective and do not maximize crop choice. There is a need for an intelligent crop recommendation system. This is supported by 7 representative gap statements extracted from 7 papers, rated moderate evidence.

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