Convolutional neural networks in computer vision for grain crop phenotyping: A review
YH Wang, WH Su - Agronomy, 2022 - mdpi.com
Computer vision (CV) combined with a deep convolutional neural network (CNN) has
emerged as a reliable analytical method to effectively characterize and quantify high …
emerged as a reliable analytical method to effectively characterize and quantify high …
Multi-omics techniques for soybean molecular breeding
P Cao, Y Zhao, F Wu, D Xin, C Liu, X Wu, J Lv… - International Journal of …, 2022 - mdpi.com
Soybean is a major crop that provides essential protein and oil for food and feed. Since its
origin in China over 5000 years ago, soybean has spread throughout the world, becoming …
origin in China over 5000 years ago, soybean has spread throughout the world, becoming …
Deep learning based soybean seed classification
Z Huang, R Wang, Y Cao, S Zheng, Y Teng… - … and Electronics in …, 2022 - Elsevier
Accurately sorting high-quality soybean seeds is a crucial and time-consuming task in
quality inspection and food safety. This paper designs a full pipeline to classify the soybean …
quality inspection and food safety. This paper designs a full pipeline to classify the soybean …
Scaling up high-throughput phenotyping for abiotic stress selection in the field
Key message High-throughput phenotyping (HTP) is in its infancy for deployment in large-
scale breeding programmes. With the ability to measure correlated traits associated with …
scale breeding programmes. With the ability to measure correlated traits associated with …
High-throughput soybean seeds phenotyping with convolutional neural networks and transfer learning
Background Effective soybean seed phenotyping demands large-scale accurate quantities
of morphological parameters. The traditional manual acquisition of soybean seed …
of morphological parameters. The traditional manual acquisition of soybean seed …
Improved field-based soybean seed counting and localization with feature level considered
J Zhao, A Kaga, T Yamada, K Komatsu, K Hirata… - Plant …, 2023 - spj.science.org
Developing automated soybean seed counting tools will help automate yield prediction
before harvesting and improving selection efficiency in breeding programs. An integrated …
before harvesting and improving selection efficiency in breeding programs. An integrated …
Deep learning-based approach using X-ray images for classifying Crambe abyssinica seed quality
AD de Medeiros, RC Bernardes, LJ da Silva… - Industrial Crops and …, 2021 - Elsevier
The application of imaging technologies combined with state-of-the-art artificial intelligence
techniques has provided important advances in the modern oilseed industry. Innovative …
techniques has provided important advances in the modern oilseed industry. Innovative …
Soybean yield estimation and its components: A linear regression approach
Soybean yield estimation is either based on yield monitors or agro-meteorological and
satellite imagery data, but they present several limiting factors regarding on-farm decision …
satellite imagery data, but they present several limiting factors regarding on-farm decision …
High-throughput phenotyping in soybean
Abstract Soybean [Glycine max (L.) Merr.] breeders and geneticists routinely evaluate
thousands of plots per year in order to characterize various accessions and breeding …
thousands of plots per year in order to characterize various accessions and breeding …
Review of machine learning and deep learning models in agriculture
Machine learning (ML) refers to the processes that enable computers to think based on
various learning methods. It can be also called domain which is a subset of Artificial …
various learning methods. It can be also called domain which is a subset of Artificial …