Crop Yield Quantity and Price Prediction: An Ensemble Approach

2021 ◽  
pp. 110-120
Author(s):  
Drashi Jain ◽  
Choudhary Nikita ◽  
Megha Kamble
Keyword(s):  
Crop Yield ◽  
Price Prediction ◽  
Ensemble Approach

K-MEANS CLUSTERING ALGORITHM BASED CLASSIFICATION OF SOIL FERTILITY IN NORTH WEST NIGERIA

2020 ◽  
Vol 4 (2) ◽  
pp. 780-787
Author(s):  
Ibrahim Hassan Hayatu ◽  
Abdullahi Mohammed ◽  
Barroon Ahmad Isma’eel ◽  
Sahabi Yusuf Ali
Keyword(s):  
Soil Fertility ◽  
Crop Yield ◽  
Clustering Algorithm ◽  
Soil Samples ◽  
North West ◽  
R Programming ◽  
Available Information ◽  
Northwest Region ◽  
The Relationship

Soil fertility determines a plant's development process that guarantees food sufficiency and the security of lives and properties through bumper harvests. The fertility of soil varies according to regions, thereby determining the type of crops to be planted. However, there is no repository or any source of information about the fertility of the soil in any region in Nigeria especially the Northwest of the country. The only available information is soil samples with their attributes which gives little or no information to the average farmer. This has affected crop yield in all the regions, more particularly the Northwest region, thus resulting in lower food production.  Therefore, this study is aimed at classifying soil data based on their fertility in the Northwest region of Nigeria using R programming. Data were obtained from the department of soil science from Ahmadu Bello University, Zaria. The data contain 400 soil samples containing 13 attributes. The relationship between soil attributes was observed based on the data. K-means clustering algorithm was employed in analyzing soil fertility clusters. Four clusters were identified with cluster 1 having the highest fertility, followed by 2 and the fertility decreases with an increasing number of clusters. The identification of the most fertile clusters will guide farmers on where best to concentrate on when planting their crops in order to improve productivity and crop yield.

Evaluation of nitrogen dynamics and crop yield in a long-term tillage experiment

2007 ◽  
Vol 35 (2) ◽  
pp. 769-772 ◽  
Author(s):  
Attila Megyes ◽  
Tamás Rátonyi ◽  
Dénes Sulyok
Keyword(s):  
Crop Yield ◽  
Nitrogen Dynamics

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

EFFECT OF FLY ASH ON CROP YIELD AND PHYSICO-CHEMICAL, MICROBIAL AND ENZYME ACTIVITIES OF SODIC SOILS

2016 ◽  
Vol 15 (11) ◽  
pp. 2433-2440 ◽  
Author(s):  
Kripal Singh ◽  
Vimal Chandra Pandey ◽  
Bajrang Singh ◽  
Dharani D. Patra ◽  
Rana P. Singh
Keyword(s):  
Fly Ash ◽  
Crop Yield ◽  
Enzyme Activities ◽  
Sodic Soils ◽  
Physico Chemical

Effects of Tillage and Phosphorus Source onLong-term Phosphorus Runoff Loss and Crop Yield

2013 ◽  
Author(s):  
Antonio P. Mallarino ◽  
Mazhar Ul Haq ◽  
Matthew J. Helmers ◽  
Joshua L. Sievers ◽  
Ryan Rusk
Keyword(s):  
Crop Yield ◽  
Phosphorus Source ◽  
Phosphorus Runoff
Sign in / Sign up

Export Citation Format

Share Document