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Woo-Jae Cho and Myongkyoon Yang
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Luana Centorame, Thomas Gasperini, Alessio Ilari, Andrea Del Gatto and Ester Foppa Pedretti
Machine learning is a widespread technology that plays a crucial role in digitalisation and aims to explore rules and patterns in large datasets to autonomously solve non-linear problems, taking advantage of multiple source data. Due to its versatility, ...
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Firozeh Solimani, Angelo Cardellicchio, Massimiliano Nitti, Alfred Lako, Giovanni Dimauro and Vito Renò
Plant phenotyping studies the complex characteristics of plants, with the aim of evaluating and assessing their condition and finding better exemplars. Recently, a new branch emerged in the phenotyping field, namely, high-throughput phenotyping (HTP). Sp...
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Hideki Maki, Valerie Lynch, Dongdong Ma, Mitchell R. Tuinstra, Masanori Yamasaki and Jian Jin
Water and nitrogen (N) are major factors in plant growth and agricultural production. However, these are often confounded and produce overlapping symptoms of plant stress. The objective of this study is to verify whether the different levels of N treatme...
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Jinnan Hu, Guo Li, Haolan Mo, Yibo Lv, Tingting Qian, Ming Chen and Shenglian Lu
The extraction and analysis of plant phenotypic characteristics are critical issues for many precision agriculture applications. An improved YOLOv5 model was proposed in this study for accurate node detection and internode length estimation of crops by u...
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Saumik Basu, Natalia Moroz, Benjamin W. Lee, Kiwamu Tanaka, Liesl Oeller, Chase W. Baerlocher and David W. Crowder
In agroecosystems, plants frequently confront multiple biotic stressors, including herbivores and pathogens. The nature of these interactions plays a crucial role in mediating the activation of plant defense mechanisms. However, induction of plant chemic...
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Anirban Jyoti Hati and Rajiv Ranjan Singh
This paper analyses the contribution of residual network (ResNet) based convolutional neural network (CNN) architecture employed in two tasks related to plant phenotyping. Among the contemporary works for species recognition (SR) and infection detection ...
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Zheng Xu, Camilo Valdes and Jennifer Clarke
Scanning technologies based on X-ray Computed Tomography (CT) have been widely used in many scientific fields including medicine, nanosciences and materials research. Considerable progress in recent years has been made in agronomic and plant science rese...
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Pasquale Tripodi, Daniele Massa, Accursio Venezia and Teodoro Cardi
Increasing the ability to investigate plant functions and structure through non-invasive methods with high accuracy has become a major target in plant breeding and precision agriculture. Emerging approaches in plant phenotyping play a key role in unravel...
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Daria D. Emekeeva, Tomiris T. Kusainova, Lev I. Levitsky, Elizaveta M. Kazakova, Mark V. Ivanov, Irina P. Olkhovskaya, Mikhail L. Kuskov, Alexey N. Zhigach, Nataliya N. Glushchenko, Olga A. Bogoslovskaya and Irina A. Tarasova
Image analysis is widely applied in plant science for phenotyping and monitoring botanic and agricultural species. Although a lot of software is available, tools integrating image analysis and statistical assessment of seedling growth in large groups of ...
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David G. Tork, Neil O. Anderson, Donald L. Wyse and Kevin J. Betts
Flaxseed has gained popularity as a health food. Wild, perennial Linum relatives of annual flax (L. usitatissimum) possess similar oil compositions, making them perennial oilseed (OS) alternatives. The objective of this study was to phenotype 25 OS and 1...
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Maria Balota, Sayantan Sarkar, Rebecca S. Bennett and Mark D. Burow
Peanut (Arachis hypogaea L.) plants respond to drought stress through changes in morpho-physiological and agronomic characteristics that breeders can use to improve the drought tolerance of this crop. Although agronomic traits, such as plant height, late...
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Allimuthu Elangovan, Nguyen Trung Duc, Dhandapani Raju, Sudhir Kumar, Biswabiplab Singh, Chandrapal Vishwakarma, Subbaiyan Gopala Krishnan, Ranjith Kumar Ellur, Monika Dalal, Padmini Swain, Sushanta Kumar Dash, Madan Pal Singh, Rabi Narayan Sahoo, Govindaraj Kamalam Dinesh, Poonam Gupta and Viswanathan Chinnusamy
Phenomics technologies have advanced rapidly in the recent past for precision phenotyping of diverse crop plants. High-throughput phenotyping using imaging sensors has been proven to fetch more informative data from a large population of genotypes than t...
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Aryuanto Soetedjo and Evy Hendriarianti
A camera vision system is a fast and effective approach to monitoring leaves. It can be used to monitor plant growth, detect diseases, and conduct plant phenotyping. However, due to the outdoor environment of plants, it becomes challenging to use. This p...
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Chengquan Zhou, Hongbao Ye, Zhifu Xu, Jun Hu, Xiaoyan Shi, Shan Hua, Jibo Yue and Guijun Yang
Leaf coverage is an indicator of plant growth rate and predicted yield, and thus it is crucial to plant-breeding research. Robust image segmentation of leaf coverage from remote-sensing images acquired by unmanned aerial vehicles (UAVs) in varying enviro...
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Haifei Hu, Armin Scheben and David Edwards
With the global human population growing rapidly, agricultural production must increase to meet crop demand. Improving crops through breeding is a sustainable approach to increase yield and yield stability without intensifying the use of fertilisers and ...
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Subhrajit Satpathy, Dipendra Shahi, Brayden Blanchard, Michael Pontif, Kenneth Gravois, Collins Kimbeng, Anna Hale, James Todd, Atmakuri Rao and Niranjan Baisakh
Sugarcane (Saccharum spp.) is an important perennial grass crop for both sugar and biofuel industries. The Louisiana sugarcane breeding program is focused on improving sugar yield by incrementally increasing genetic gain. With the advancement in genotypi...
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