Regarding crop recommendation ?

Yaganteeswarudu Akkem

1) Market for the suggested agricultural product, financial issues (credits), local experience of cultivation for the chosen crop

2) Climate pattern (min, max, average, sum of positive temperatures (>10, >15, >20oC) during vegetation period, rains, extreme weather conditions, dinamics of water in soil during vegetation, chance for irrigation)

3) Soil pH, mechanic structure, fertility, chance for correction by cultivation

4) Weeds, pests, diseases

5) available agrotechnology (soil cultivation, plant protection, fertilization, harvesting, harvest storage, transportation to market, skilled labor)

6) other crops in crop rotation

7) Cultivars/seeds /planting material of high quality suitable for local area

J. C. Tarafdar

The attached file may be useful to you.

Ahmad Al Khraisat

Research objectives in crop recommendation can encompass a wide range of topics and can be interdisciplinary in nature, combining knowledge from fields such as agronomy, horticulture, soil science, climatology, and data science. Some examples of research objectives in crop recommendation include:

Developing models to predict crop yields based on a variety of factors such as climate, soil type, and planting conditions.

Developing methods for selecting the best crop for a specific region based on climate and soil conditions.

Investigating the impact of different farming practices on crop yields, such as irrigation, fertilization, and pest management.

Developing decision support systems for farmers to aid in crop selection and management.

Studying the effectiveness of precision agriculture techniques for crop recommendation and yield prediction.

Investigating the use of remote sensing data for crop recommendation and yield prediction.

Studying the influence of socioeconomic factors, such as market demand, on crop selection.

Examining the potential for using machine learning and artificial intelligence to improve crop recommendation systems.

Here are a few articles that may be of interest in the area of crop recommendation:

N. M. Gerdes, L. R. Olds, J. C. Olenczuk, "Agricultural Yield Prediction and Decision Support Systems: A Review of Methods and Applications." Agronomy Journal, 2010.

M. S. Khan, Z. M. A. Baig, M. A. Sheikh, "An Overview of Precision Agriculture Techniques for Crop Yield Prediction and Management." Precision Agriculture, 2016.

J. Han, M. Kwasniewski, "A Review of Machine Learning Techniques for Crop Yield Prediction." Computers and Electronics in Agriculture, 2016.

Z. Wang, Y. Liu, X. Zhang, "Crop Recommendation System Based on Decision Tree Algorithm." American Journal of Plant Sciences, 2016.

S. J. Tarquini, R. A. Ferrarese, J. L. Ponzoni, "A Review of Crop Recommendation Systems for Precision Agriculture." Journal of Agricultural Science, 2015.

Ahmad Al Khraisat

There are several areas in crop recommendation where research can be conducted:

Crop suitability based on soil and climatic conditions: Research can be done to develop models that can recommend crops suitable for specific soil and climatic conditions. This can be done by analyzing the soil and weather data, and using machine learning algorithms to determine which crops are most suitable for a given location.

Precision agriculture: Research can be done to develop recommendations for farmers based on real-time data from sensors, drones, and other sources. This can help farmers make more informed decisions about which crops to plant, when to plant them, and how to manage them.

Nutrient management: Research can be done to develop crop recommendations based on soil nutrient levels and the nutrient requirements of different crops. This can help farmers make decisions about fertilization and other nutrient management practices.

Drought tolerance: Research can be done to develop recommendations for crops that are more drought-tolerant, which can be important for farmers in areas that are prone to drought.

Climate change: Research can be done to assess the impacts of climate change on crop productivity, and to develop recommendations for crops that are better able to adapt to changing weather patterns.

Research articles on crop recommendation:

"Crop suitability mapping using climate data and GIS" by M. K. Ali, A. M. Alshehri, and M. S. Al-Zahrani (2015)

"Precision Agriculture for Improved Crop Management" by B. G. Langton, J. R. Kiniry, and D. D. Bullock (2017)

"Soil nutrient management for sustainable crop production" by K. J. Biradar, R. K. Shukla, and S. K. Chaturvedi (2017)

"Drought tolerance in crops: physiological and molecular perspectives" by R. M. F. Leegood and P. S. John (2019)

"Impact of Climate Change on Crop Productivity: A Review" by R. T. N. Kumar, S. S. Choudhary, and M. K. Yadav (2017)

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