A systematic literature review on crop yield prediction with deep learning and remote sensing
Deep learning has emerged as a potential tool for crop yield prediction, allowing the model
to automatically extract features and learn from the datasets. Meanwhile, smart farming …
to automatically extract features and learn from the datasets. Meanwhile, smart farming …
Emerging trends in machine learning to predict crop yield and study its influential factors: A survey
Agriculture is one of the most crucial field contributing to the development of any nation. It
not only affects the economy of nation but also has impact on the world food grain statistics …
not only affects the economy of nation but also has impact on the world food grain statistics …
Transfer-learning-based approach for leaf chlorophyll content estimation of winter wheat from hyperspectral data
Leaf chlorophyll, as a key factor for carbon circulation in the ecosystem, is significant for the
photosynthetic productivity estimation and crop growth monitoring in agricultural …
photosynthetic productivity estimation and crop growth monitoring in agricultural …
Combining multi-source data and machine learning approaches to predict winter wheat yield in the conterminous United States
Winter wheat (Triticum aestivum L.) is one of the most important cereal crops, supplying
essential food for the world population. Because the United States is a major producer and …
essential food for the world population. Because the United States is a major producer and …
Deep learning based wheat crop yield prediction model in Punjab region of North India
Crop yield prediction is an important aspect of agriculture. The timely and accurate crop
yield predictions can be of great help for policy makers and farmers in planning and decision …
yield predictions can be of great help for policy makers and farmers in planning and decision …
Suitability of satellite remote sensing data for yield estimation in northeast Germany
C Vallentin, K Harfenmeister, S Itzerott… - Precision …, 2022 - Springer
Abstract Information provided by satellite data is becoming increasingly important in the field
of agriculture. Estimating biomass, nitrogen content or crop yield can improve farm …
of agriculture. Estimating biomass, nitrogen content or crop yield can improve farm …
[HTML][HTML] Deciphering the contributions of spectral and structural data to wheat yield estimation from proximal sensing
Accurate, efficient, and timely yield estimation is critical for crop variety breeding and
management optimization. However, the contributions of proximal sensing data …
management optimization. However, the contributions of proximal sensing data …
Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS): Part III. Versatile applications
In this review, the comprehensive summary of two-dimensional correlation spectroscopy (2D-
COS) for the last two years is covered. The remarkable applications of 2D-COS in diverse …
COS) for the last two years is covered. The remarkable applications of 2D-COS in diverse …
The classification performance and mechanism of machine learning algorithms in winter wheat mapping using Sentinel-2 10 m resolution imagery
P Fang, X Zhang, P Wei, Y Wang, H Zhang, F Liu… - Applied Sciences, 2020 - mdpi.com
Featured Application Machine learning algorithms are essential to crop identification and
land use/cover. Our work indicates that compared to RF and CART algorithms, SVM …
land use/cover. Our work indicates that compared to RF and CART algorithms, SVM …
[HTML][HTML] Development of optimized phenomic predictors for efficient plant breeding decisions using phenomic-assisted selection in soybean
K Parmley, K Nagasubramanian, S Sarkar… - Plant …, 2019 - spj.science.org
The rate of advancement made in phenomic-assisted breeding methodologies has lagged
those of genomic-assisted techniques, which is now a critical component of mainstream …
those of genomic-assisted techniques, which is now a critical component of mainstream …