Crop Recommendation System for Precision Agriculture

2019 ◽  
Vol 7 (5) ◽  
pp. 1277-1282
Author(s):  
Bharath Kumar R ◽  
Balakrishna K ◽  
Bency Celso A ◽  
Siddesha M ◽  
Sushmitha R
Keyword(s):  
Precision Agriculture ◽  
Recommendation System

scholarly journals Online Fertilizer Recommendation System (OFRS): A Step Towards Precision Agriculture And Optimized Fertilizer Usage By Smallholder Farmers In Bangladesh

2020 ◽  
Vol 1 (4) ◽  
Author(s):  
M. A. Hossain ◽  
M. N. A. Siddique
Keyword(s):  
Precision Agriculture ◽  
Recommendation System ◽  
Smallholder Farmers ◽  
Fertilizer Application ◽  
Soil Test ◽  
Total Production ◽  
Soil Database ◽  
Fertilizer Recommendation ◽  
Fertilizer Recommendations ◽  
Input Cost

The recent progression and Green Revolution (approx. between the 1990s-2010s) in agriculture of Bangladesh resulted in an increase of total production despite yield-gap to ensure food security. But agriculture in Bangladesh is still backed-up by higher use of inputs (agrochemicals-fertilizers, pesticides; modern varieties, irrigation etc.) and inversion tillage. This conventional agrochemical-based smallholder agriculture may lead to soil and environmental degradation, soil acidification, and a decline in soil fertility. Therefore, it is significant to optimize input application in intensive agriculture, especially fertilizers. This paper introduces the potential online facilities of generating online fertilizer recommendations for smallholder farmers in Bangladesh to ensure proper usage of fertilizers and enable sustainable agricultural production. We also highlighted how the usage of fertilizers increased with an increase in total production over time. But the sustainability of production in the years to come still remain challenging. With the aim of sustainable crop production, reduction in the misuse of fertilizers and reduction of input cost by optimizing the present pattern of excessive fertilizer application, the Soil Resource Development Institute (SRDI) provides location-specific fertilizer recommendation through both the manual and soil test based interpretation of plant nutrients: soil database in Upzazila Nirdeshika and static laboratory soil analysis. Recently, SRDI developed web-based software named Online Fertilizer Recommendation System (OFRS). The system is capable of generating location-specific fertilizer recommendations for selected crops by analyzing the national soil database developed by this governmental institute. The software requires farmer field location, respective soil and land type, and crop type and variety information to generate crop-specific instant fertilizer recommendation. It was observed that by using fertilizer according to the recommended dose calculated on the basis of soil test values, farmers could harvest approx. 7-22% higher yield of different crops over usual farmers practice. If this system can be popularized and disseminated by effective agricultural extension, this would immensely contribute to the promotion of precision agriculture, input cost reduction and it would certainly enable us to optimize fertilizer application by the smallholder farmers in Bangladesh.

Prediction of Crop, Fertilizer and Disease Detection for Precision Agriculture

2021 ◽  
Vol 9 (10) ◽  
pp. 26-30
Author(s):  
Bharathi C
Keyword(s):  
Data Mining ◽  
Pest Control ◽  
Precision Agriculture ◽  
Recommendation System ◽  
Infected Leaf ◽  
Crop Choice ◽  
Fertilizer Recommendation ◽  
Modern Technique ◽  
Using Data ◽  
The Right

Abstract: The main walk of life of our Country is Agriculture. More than 70 % of the population’s lives depend upon agriculture. It is also a great source of country’s economy. In order to make this filed more profitable for farmers proper crops have to be grown in their fields. The prevalent problem among the farmers is Crop choice depending upon the soil in their farmlands. Another challenge faced by farmers is choosing the right fertilisers for their crops, which plays a very important role in getting a good and profitable yield. There is another major problem which they have to give more attention is the pest control or the diseases to which the plants may limit their growth. The above listed problems may solved using the advanced techniques of Precision Agriculture and data mining. Precision Agriculture is modern technique which can be used for farming. The main objective of is to solve above problems using data mining techniques and build a decision system which would help farmers to choose right crops for their farm , fertiliser recommendation for the crops grown and also to help the farmers in detecting the diseases by using the infected leaf images.. Keywords: Precision Agriculture, Data Mining, Crop, fertilizer recommendation system, ML Algorithms

scholarly journals Crop Recommendation System to Maximize Crop Yield in Ramtek region using Machine Learning

2019 ◽  
pp. 485-489
Author(s):  
D. Anantha Reddy ◽  
Bhagyashri Dadore ◽  
Aarti Watekar
Keyword(s):  
Crop Yield ◽  
Precision Agriculture ◽  
Recommendation System ◽  
Statistical Data ◽  
Weather Condition ◽  
Ground Truth ◽  
Majority Voting ◽  
Soil Parameters ◽  
Yield Data ◽  
Yield State

In Indian economy and employment agriculture plays major role. The most common problem faced by the Indian farmers is they do not opt crop based on the necessity of soil, as a result they face serious setback in productivity. This problem can be addressed through precision agriculture. This method takes three parameters into consideration, viz: soil characteristics, soil types and crop yield data collection based on these parameters suggesting the farmer suitable crop to be cultivated. Precision agriculture helps in reduction of non suitable crop which indeed increases productivity, apart from the following advantages like efficacy in input as well as output and better decision making for farming. This method gives solutions like proposing a recommendation system through an ensemble model with majority voting techniques using random tree, CHAID, K _ Nearest Neighbour and Naive Bayes as learner to recommend suitable crop based on soil parameters with high specific accuracy and efficiency. The classified image generated by these techniques consists of ground truth statistical data and parameters of it are weather, crop yield, state and district wise crops to predict the yield of a particular crop under particular weather condition.

scholarly journals Crop Recommendation using Machine Learning Techniques

2019 ◽  
Vol 9 (2S) ◽  
pp. 658-661
Keyword(s):  
Machine Learning ◽  
Precision Agriculture ◽  
Climatic Condition ◽  
Recommendation System ◽  
Soil Characteristics ◽  
Data Driven ◽  
Machine Learning Techniques ◽  
Traditional Farming ◽  
Learning Techniques ◽  
The Right

Precision agriculture (PA) allows precise utilization of inputs like seed, water, pesticides, and fertilizers at the right time to the crop for maximizing productivity, quality and yields. By deploying sensors and mapping fields, farmers can understand their field in a better way conserve the resources being used and reduce adverse affects on the environment. Most of the Indian farmers practice traditional farming patterns to decide crop to be cultivated in a field. However, the farmers do not perceive crop yield is interdependent on soil characteristics and climatic condition. Thus this paper proposes a crop recommendation system which helps farmers to decide the right crop to sow in their field. Machine learning techniques provide efficient framework for data-driven decision making. This paper provides a review on set of machine learning techniques to support the farmers in making decision about right crop to grow depending on their field’s prominent attributes.

Crop recommendation system for precision agriculture

2017 ◽  
Author(s):  
S. Pudumalar ◽  
E. Ramanujam ◽  
R. Harine Rajashree ◽  
C. Kavya ◽  
T. Kiruthika ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Recommendation System

Analysis on Research Paper Publication Recommendation System with Composition of Papers and Conferences Matrices

2020 ◽  
pp. 120-127
Author(s):  
Htay Htay Win ◽  
Aye Thida Myint ◽  
Mi Cho Cho
Keyword(s):  
Social Network ◽  
Dimensionality Reduction ◽  
Correspondence Analysis ◽  
Recommendation System ◽  
Research Paper ◽  
Topic Modelling ◽  
Research Papers ◽  
The Right ◽  
Publication Recommendation

For years, achievements and discoveries made by researcher are made aware through research papers published in appropriate journals or conferences. Many a time, established s researcher and mainly new user are caught up in the predicament of choosing an appropriate conference to get their work all the time. Every scienti?c conference and journal is inclined towards a particular ?eld of research and there is a extensive group of them for any particular ?eld. Choosing an appropriate venue is needed as it helps in reaching out to the right listener and also to further one’s chance of getting their paper published. In this work, we address the problem of recommending appropriate conferences to the authors to increase their chances of receipt. We present three di?erent approaches for the same involving the use of social network of the authors and the content of the paper in the settings of dimensionality reduction and topic modelling. In all these approaches, we apply Correspondence Analysis (CA) to obtain appropriate relationships between the entities in question, such as conferences and papers. Our models show hopeful results when compared with existing methods such as content-based ?ltering, collaborative ?ltering and hybrid ?ltering.

Environmental Benefits of Precision Agriculture Adoption

2020 ◽  
pp. 637-656 ◽  
Author(s):  
Marco Medici ◽  
Søren Marcus Pedersen ◽  
Giacomo Carli ◽  
Maria Rita Tagliaventi
Keyword(s):  
Environmental Impacts ◽  
Precision Agriculture ◽  
New Technologies ◽  
Environmental Benefits ◽  
Herbicide Application ◽  
Pesticide Application ◽  
Policy Makers ◽  
Application Rates ◽  
Biodiversity Policy ◽  
Lime Application

The purpose of this study is to analyse the environmental benefits of precision agriculture technology adoption obtained from the mitigation of negative environmental impacts of agricultural inputs in modern farming. Our literature review of the environmental benefits related to the adoption of precision agriculture solutions is aimed at raising farmers' and other stakeholders' awareness of the actual environmental impacts from this set of new technologies. Existing studies were categorised according to the environmental impacts of different agricultural activities: nitrogen application, lime application, pesticide application, manure application and herbicide application. Our findings highlighted the effects of the reduction of input application rates and the consequent impacts on climate, soil, water and biodiversity. Policy makers can benefit from the outcomes of this study developing an understanding of the environmental impact of precision agriculture in order to promote and support initiatives aimed at fostering sustainable agriculture.

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