Crop Yield Estimation Using Machine Learning

2021 ◽  
pp. 328-342
Author(s):  
Nihar Patel ◽  
Deep Patel ◽  
Samir Patel ◽  
Vibha Patel
Keyword(s):  
Machine Learning ◽  
Crop Yield ◽  
Yield Estimation

scholarly journals ML Methods for Crop Yield Prediction and Estimation: An Exploration

2020 ◽  
Vol 9 (3) ◽  
pp. 3506-3508
Keyword(s):  
Machine Learning ◽  
Detailed Analysis ◽  
Crop Yield ◽  
Learning Process ◽  
Machine Learning Techniques ◽  
Yield Prediction ◽  
Yield Estimation ◽  
Data Set ◽  
Yield Optimization ◽  
Learning Techniques

Machine learning Has performed a essential position within the estimation of crop yield for both farmers and consumers of the products. Machine learning techniques learn from data set related to the environment on which the estimations and estimation are to be made and the outcome of the learning process are used by farmers for corrective measures for yield optimization. This paper we explore various ML techniques utilized in crop yield estimation and provide the detailed analysis of accuracy of the techniques.

Multisensor crop yield estimation with machine learning

2020 ◽  
Author(s):  
Laura Martínez Ferrer ◽  
Maria Piles ◽  
Gustau Camps-Valls
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Linear Regression ◽  
Crop Yield ◽  
Gaussian Processes ◽  
Vegetation Index ◽  
Maximum Temperature ◽  
Yield Estimation ◽  
Study Results ◽  
Non Linear

<p>Providing accurate and spatially resolved predictions of crop yield is of utmost importance due to the rapid increase in the demand of biofuels and food in the foreseeable future. Satellite based remote sensing over agricultural areas allows monitoring crop development through key bio-geophysical variables such as the Enhanced Vegetation Index (EVI), sensitive to canopy greenness, the Vegetation Optical Depth (VOD), sensitive to biomass water-uptake dynamics, and Soil Moisture (SM), which provides direct information of plant available water. The aim of this work is to implement an automatic system for county-based crop yield estimation using time series from multisource satellite observations, meteorological data and available in situ surveys as supporting information. The spatio-temporal resolution of satellite and meteorological observations are fully exploited and synergistically combined for crop yield prediction using machine learning models. Linear and non-linear regression methods are used: least squares, LASSO, random forests, kernel machines and Gaussian processes. Here we are not only interested in the prediction skill, but also on understanding the relative relevance of the covariates. For this, we first study the importance of each feature separately and then propose a global model for operational monitoring of crop status using the most relevant agro-ecological drivers.</p><p> </p><p>We selected the Continental U.S. and a four-year time series dataset to perform the research study. Results reveal that the three satellite variables are complementary and that their combination with maximum temperature and precipitation from meteorological stations provides the best estimations. Interestingly, adding information about crop planted area also improved the predictions. A non-linear regression model based on Gaussian processes led to best results for all considered crops (soybean, corn and wheat), with high accuracy (low bias and correlation coefficients ranging from 0.75 to 0.92). The feature ranking allowed understanding the main drivers for crop monitoring and the underlying factors behind a prediction loss or gain.</p>

Analysis of agricultural crop yield prediction using statistical techniques of machine learning

2021 ◽  
Author(s):  
Janmejay Pant ◽  
R.P. Pant ◽  
Manoj Kumar Singh ◽  
Devesh Pratap Singh ◽  
Himanshu Pant
Keyword(s):  
Machine Learning ◽  
Crop Yield ◽  
Statistical Techniques ◽  
Yield Prediction ◽  
Agricultural Crop

scholarly journals Date Palm Crop Yield Estimation – A Framework

2019 ◽  
Vol 7 (6) ◽  
pp. 143-146
Author(s):  
Dr. Mohammad Husain ◽  
Dr. Rafi Ahmad Khan
Keyword(s):  
Crop Yield ◽  
Date Palm ◽  
Yield Estimation
Sign in / Sign up

Export Citation Format

Share Document