To put you in the context, our work consists in realizing a machine learning model which takes a vector with the properties of a farm, includes the weather why not.Then from a database of crops, make a recommendation of the most suitable crop for the soil. Therefore a recognition on the elements which help in this decision is an important part before starting the collection of the data necessary for the model.
@ Hicham, I think soil nutrient status, environmental suitability of the crop, marketing avenues and demand of the crop, water resources if crops are irrigated are the main elements that should consider to recommend a crop for a particular area.
I agree with you Tarafdar. In general its the environmental conditions including the genetic make up......
I think the main factors are your soil and agro climatic conditions. Other minor or secondary factors could be the demond, market value etc.
Environmental conditions, soil type are the main elements that recommend the crop for an particular area.
The main factor influencing the choice of a crop is its marketing. If there is a scope of getting good price for the produce, then surely the farmer will adopt it. Like in Punjab, there is an assured marketing of Rice and Wheat, hence the maximum area is under these crops. The irrigation factor is another thing to be considered; it influences our decision for crop selection. Rice being a high water demanding crop cannnot be grown where there are less irrigation facilities through groundwater or canal water. Hence, farmers prefer cotton crop over rice in such areas. The soil pH and texture also influence the recommendation system. Direct seeded rice is recommended over only medium to heavy soils and not in case of light soils. If the soil is alkaline, then special varieties need to be cultivated or any other alternative crop needs to be grown which can withstand alkalinity.
Nitrogen (N) fertilizer must be used judiciously to maximize profits, reduce the susceptibility to diseases and pests, optimize crop quality, save energy, and protect the environment. N can be saved by using correct N recommendations. Research indicates that recommendations may be too high when based on uncritically chosen regression models. Weather and climatic conditions also play a significant role in agricultural activities.
Some crops are very labour-intensive. Some crops require more skill than others. Some crops are more risky than others (high profit if it's a good year but high chance of crop failure if the weather is bad), and some farmers are more able to cope with those risks.
Presence or absence of pests might be important.
I would like to recommend you to go through two of my articles:
1. B.K.Tripathy and Sooraj, T. R.: An Interval Valued Fuzzy Soft set Based Optimization Algorithm for High Yielding Seed Selection, International Journal of Fuzzy Sets and Applications, IGI publications, vol.7, issue 2, (2018), pp. 44 - 61.
2. B.K.Tripathy, Sooraj, T. R.: Optimization of seed selection for higher product using Interval valued Hesitant Fuzzy Soft Sets, Songklanakarin Journal of Science and Technology (SJST), 40 (5), Sep. -Oct. 2018, (2018), pp.1125-1135 .
I suggest you follow https://towardsdatascience.com/introduction-to-recommender-systems-6c66cf15ada
Recommendations for crop suitability must be based on a crops soil, nutrient and climatic requirements. Access to inputs and markets can be considered also.
First of all, ensuring optimal moisture reserves in the soil. The rest is fixable without special costs for production and science.
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