Automation in agriculture by machine and deep learning techniques: A review of recent developments
Recently, agriculture has gained much attention regarding automation by artificial
intelligence techniques and robotic systems. Particularly, with the advancements in machine …
intelligence techniques and robotic systems. Particularly, with the advancements in machine …
Deep learning for plant stress phenotyping: trends and future perspectives
Deep learning (DL), a subset of machine learning approaches, has emerged as a versatile
tool to assimilate large amounts of heterogeneous data and provide reliable predictions of …
tool to assimilate large amounts of heterogeneous data and provide reliable predictions of …
[HTML][HTML] High-throughput phenotyping: Breaking through the bottleneck in future crop breeding
P Song, J Wang, X Guo, W Yang, C Zhao - The Crop Journal, 2021 - Elsevier
With the rapid development of genetic analysis techniques and crop population size,
phenotyping has become the bottleneck restricting crop breeding. Breaking through this …
phenotyping has become the bottleneck restricting crop breeding. Breaking through this …
Strawberry yield prediction based on a deep neural network using high-resolution aerial orthoimages
Strawberry growers in Florida suffer from a lack of efficient and accurate yield forecasts for
strawberries, which would allow them to allocate optimal labor and equipment, as well as …
strawberries, which would allow them to allocate optimal labor and equipment, as well as …
Deep learning: As the new frontier in high-throughput plant phenotyping
S Arya, KS Sandhu, J Singh, S Kumar - Euphytica, 2022 - Springer
With climate change and ever-increasing population growth, the pace of varietal
development needs to be accelerated in order to feed a population of 10 billion by 2050 …
development needs to be accelerated in order to feed a population of 10 billion by 2050 …
Robotic technologies for high-throughput plant phenotyping: Contemporary reviews and future perspectives
Phenotyping plants is an essential component of any effort to develop new crop varieties. As
plant breeders seek to increase crop productivity and produce more food for the future, the …
plant breeders seek to increase crop productivity and produce more food for the future, the …
Identifying crop water stress using deep learning models
The identification of water stress is a major challenge for timely and effective irrigation to
ensure global food security and sustainable agriculture. Several direct and indirect methods …
ensure global food security and sustainable agriculture. Several direct and indirect methods …
[HTML][HTML] Cyber-agricultural systems for crop breeding and sustainable production
The cyber-agricultural system (CAS) represents an overarching framework of agriculture that
leverages recent advances in ubiquitous sensing, artificial intelligence, smart actuators, and …
leverages recent advances in ubiquitous sensing, artificial intelligence, smart actuators, and …
[HTML][HTML] A review of high-throughput field phenotyping systems: focusing on ground robots
Manual assessments of plant phenotypes in the field can be labor-intensive and inefficient.
The high-throughput field phenotyping systems and in particular robotic systems play an …
The high-throughput field phenotyping systems and in particular robotic systems play an …
IoFT-FIS: Internet of farm things based prediction for crop pest infestation using optimized fuzzy inference system
Advanced farming techniques help to know the appropriate environmental conditions, soil
quality, water and fertilizer needs, and crop monitoring during each plant's growth phase …
quality, water and fertilizer needs, and crop monitoring during each plant's growth phase …