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1. Accurate Identification of Pine Wood Nematode Disease with a Deep Convolution Neural Network

Author:
Jixia Huang; Xiao Lu; Liyuan Chen; Hong Sun; Shaohua Wang; Guofei Fang
Source:
Remote Sensing 2022 v.14 no.4 pp. -
ISSN:
2072-4292
Subject:
disease detection,   etc   ; Bursaphelenchus xylophilus; data collection;     Show all 3 Subjects
Abstract:
... Pine wood nematode disease is a devastating pine disease that poses a great threat to forest ecosystems. The use of remote sensing methods can achieve macroscopic and dynamic detection of this disease; however, the efficiency and accuracy of traditional remote sensing image recognition methods are not always sufficient for disease detection. Deep convolutional neural networks (D-CNNs), a technolog ...
DOI:
10.3390/rs14040913

2. RS-Net: robust segmentation of green overlapped apples

Author:
Weikuan Jia; Zhonghua Zhang; Wenjiang Shao; Ze Ji; Sujuan Hou
Source:
Precision agriculture 2022 v.23 no.2 pp. 492-513
ISSN:
1385-2256
Subject:
disease detection,   etc   ; fruits; models; precision agriculture; vision;     Show all 5 Subjects
Abstract:
... Fruit detection and segmentation will be essential for future agronomic management, with applications in yield estimation, growth monitoring, intelligent picking, disease detection and etc. In order to more accurately and efficiently realize the recognition and segmentation of apples in natural orchards, a robust segmentation net framework specially developed for fruit production is proposed. This ...
DOI:
10.1007/s11119-021-09846-3

3. Instance-Aware Plant Disease Detection by Utilizing Saliency Map and Self-Supervised Pre-Training

Author:
Taejoo Kim; Hyeongjun Kim; Kyeonghoon Baik; Yukyung Choi
Source:
Agriculture (Basel) 2022 v.12 no.8 pp. -
ISSN:
2077-0472
Subject:
disease detection,   etc   ; agricultural productivity; agriculture; crop quality; data collection; models;     Show all 6 Subjects
Abstract:
... Plant disease detection is essential for optimizing agricultural productivity and crop quality. With the recent advent of deep learning and large-scale plant disease datasets, many studies have shown high performance of supervised learning-based plant disease detectors. However, these studies still have limitations due to two aspects. First, labeling cost and class imbalance problems remain challe ...
DOI:
10.3390/agriculture12081084

4. A new method for broadening the detection range of immunoassay and its application in β-hCG quantitative detection

Author:
Bei Zhang; Miao Guo; Tianjie Zhang; Dandan Liu; Xin Tan; Xue Li; Yang Yu; Huiqiang Li
Source:
Analytical methods 2022 v.14 no.15 pp. 1515-1522
ISSN:
1759-9679
Subject:
disease detection,   etc   ; detection limit; embryogenesis; immunoassays; luminescent assay; prediction; pregnancy;     Show all 7 Subjects
Abstract:
... Early pregnancy prediction requires very high β-hCG detection sensitivity, while embryonic development monitoring and trophoblastic disease detection require a wider detection range. In this study, based on light-initiated chemiluminescence assay (LICA), one high-affinity mAb and one low-affinity mAb were selected and coated on chemibeads with a larger coating area in different ratios to immobiliz ...
DOI:
10.1039/d2ay00220e

5. AI-Assisted Vision for Agricultural Robots

Author:
Spyros Fountas; Ioannis Malounas; Loukas Athanasakos; Ioannis Avgoustakis; Borja Espejo-Garcia
Source:
AgriEngineering 2022 v.4 no.3 pp. 674-694
ISSN:
2624-7402
Subject:
disease detection,   etc   ; algorithms; artificial intelligence; environmental impact; labor; phenotype; vision; weeds;     Show all 8 Subjects
Abstract:
... Robotics has been increasingly relevant over the years. The ever-increasing demand for productivity, the reduction of tedious labor, and safety for the operator and the environment have brought robotics to the forefront of technological innovation. The same principle applies to agricultural robots, where such solutions can aid in making farming easier for the farmers, safer, and with greater margi ...
DOI:
10.3390/agriengineering4030043

6. Advances in nanosensors for cardiovascular disease detection

Author:
Xiaofang Tang; Yaping Zhu; Weijiang Guan; Wenjuan Zhou; Peifa Wei
Source:
Life sciences 2022 v.305 pp. 120733
ISSN:
0024-3205
Subject:
disease detection,   etc   ; biomarkers; cardiovascular diseases; electrochemistry; morbidity; mortality; prediction; sensors (equipment);     Show all 8 Subjects
Abstract:
... Cardiovascular diseases (CVDs) are a leading cause of morbidity and mortality around the world. The physiological or pathological processes of CVDs can be well indicated by timely and accurate diagnosis of relevant biomarkers and function parameters. Nanosensors integrating the advantages of nanomaterials and sensing platforms have shown good potential for rapid diagnosis of CVDs, especially for e ...
DOI:
10.1016/j.lfs.2022.120733

7. Early Discrimination and Prediction of C. fimbriata-Infected Sweetpotatoes during the Asymptomatic Period Using Electronic Nose

Author:
Jiawen Wu; Linjiang Pang; Xiaoqiong Zhang; Xinghua Lu; Liqing Yin; Guoquan Lu; Jiyu Cheng
Source:
Foods 2022 v.11 no.13 pp. -
ISSN:
2304-8158
Subject:
disease detection,   etc   ; chemometrics; discriminant analysis; electronic nose; prediction; sweet potatoes; toxicity;     Show all 7 Subjects
Abstract:
... Sweetpotato is prone to disease caused by C. fimbriata without obvious lesions on the surface in the early period of infection. Therefore, it is necessary to explore the possibility of developing an efficient early disease detection method for sweetpotatoes that can be used before symptoms are observed. In this study, sweetpotatoes were inoculated with C. fimbriata and stored for different lengths ...
DOI:
10.3390/foods11131919

8. Multiscale vapor-mediated dendritic pattern formation and bacterial aggregation in complex respiratory biofluid droplets

Author:
Omkar Hegde; Ritika Chatterjee; Abdur Rasheed; Dipshikha Chakravortty; Saptarshi Basu
Source:
Journal of colloid and interface science 2022 v.606 pp. 2011-2023
ISSN:
0021-9797
Subject:
disease detection,   etc   ; direct contact; droplets; ethanol; glass; hydrodynamics; pathogenesis; topology; viability;     Show all 9 Subjects
Abstract:
... Deposits of biofluid droplets on surfaces (such as respiratory droplets formed during an expiratory) are composed of water-based salt-protein solution that may also contain an infection (bacterial/viral). The final patterns of the deposit formed and bacterial aggregation on the deposits are dictated by the fluid composition and flow dynamics within the droplet. This work reports the spatio-tempora ...
DOI:
10.1016/j.jcis.2021.09.158

9. Detection of maize tassels for UAV remote sensing image with an improved YOLOX model

Author:
Chao-yu SONG; Fan ZHANG; Jian-sheng LI; Jin-yi XIE; Chen YANG; Hang ZHOU; Jun-xiong ZHANG
Source:
Journal of integrative agriculture 2022 pp. -
ISSN:
2095-3119
Subject:
disease detection,   etc   ; agriculture; color; corn; data collection; models; unmanned aerial vehicles; vision;     Show all 8 Subjects
Abstract:
... Maize tassels detection is essential for future agronomic management in maize planting and breeding, with application in yield estimation, growth monitoring, intelligent picking, disease detection, etc. Nevertheless, some problems are gradually becoming more prominent for it. Maize tassels shown in the field are widespread occlusions and differ in size and the morphological color of different grow ...
DOI:
10.1016/j.jia.2022.09.021

10. Plant Disease Detection and Classification Method Based on the Optimized Lightweight YOLOv5 Model

Author:
Haiqing Wang; Shuqi Shang; Dongwei Wang; Xiaoning He; Kai Feng; Hao Zhu
Source:
Agriculture (Basel) 2022 v.12 no.7 pp. -
ISSN:
2077-0472
Subject:
disease detection,   etc   ; agriculture; data collection; disease control; disease diagnosis; models; weight loss;     Show all 7 Subjects
Abstract:
... Traditional plant disease diagnosis methods are mostly based on expert diagnosis, which easily leads to the backwardness of crop disease control and field management. In this paper, to improve the speed and accuracy of disease classification, a plant disease detection and classification method based on the optimized lightweight YOLOv5 model is proposed. We propose an IASM mechanism to improve the ...
DOI:
10.3390/agriculture12070931

11. An improved YOLOv5-based vegetable disease detection method

Author:
Jiawei Li; Yongliang Qiao; Sha Liu; Jiaheng Zhang; Zhenchao Yang; Meili Wang
Source:
Computers and electronics in agriculture 2022 v.202 pp. 107345
ISSN:
0168-1699
Subject:
disease detection,   etc   ; agriculture; algorithms; cash crops; electronics; food security; industry; models; vegetables;     Show all 9 Subjects
Abstract:
... The vegetable is the most dynamic cash crop in the cultivation industry, and vegetable diseases are closely related to food security. Due to the characteristics of different diseases being similar and interference from the external environment, it makes difficult to detect vegetable diseases. Therefore, we propose an improved algorithm for vegetable disease detection based on YOLOv5s. The CSP, FPN ...
DOI:
10.1016/j.compag.2022.107345

12. Early diagnosis of rice plant disease using machine learning techniques

Author:
Mayuri Sharma; Chandan Jyoti Kumar; Aniruddha Deka
Source:
Archiv für Phytopathologie und Pflanzenschutz 2022 v.55 no.3 pp. 259-283
ISSN:
1477-2906
Subject:
disease detection,   etc   ; agricultural research; blast disease; blight; data collection; early diagnosis; rice;     Show all 7 Subjects
Abstract:
... There is an incredible progress in machine learning applications in the field of agricultural research. Detection of various diseases, deficiencies, and factors impacting crops’ productivity is one of the major ongoing research in this field. This paper considers various machine learning and deep learning techniques (transfer learning) for rice disease detection. In this study three different rice ...
DOI:
10.1080/03235408.2021.2015866

13. Development of a simple and flexible enzyme‐based platform for the colorimetric detection of multiple biomarkers in non‐conventional biofluids

Author:
Alonso Ornelas‐González; Mirna González‐González; Marco Rito‐Palomares
Source:
Journal of chemical technology and biotechnology 2022 v.97 no.8 pp. 1959-1965
ISSN:
0268-2575
Subject:
disease detection,   etc   ; biomarkers; biotechnology; calibration; colorimetry; enzymes; equipment; galactose; glucose; pH; uric acid;     Show all 11 Subjects
Abstract:
... BACKGROUND: Enzyme‐based colorimetric systems are inexpensive, simple, adaptable and sensitive methods that allow specific quantification of a substrate. In the clinical field, their use has been the basis for the development of equipment and devices that today are key for disease detection. The objective of this project was to demonstrate the flexibility of a previously developed multi‐enzyme sys ...
DOI:
10.1002/jctb.7143

14. Advanced Technology in Agriculture Industry by Implementing Image Annotation Technique and Deep Learning Approach: A Review

Author:
Normaisharah Mamat; Mohd Fauzi Othman; Rawad Abdoulghafor; Samir Brahim Belhaouari; Normahira Mamat; Shamsul Faisal Mohd Hussein
Source:
Agriculture (Basel) 2022 v.12 no.7 pp. -
ISSN:
2077-0472
Subject:
disease detection,   etc   ; agricultural industry; agricultural productivity; agriculture; brain; humans; labor; neural networks; prediction;     Show all 9 Subjects
Abstract:
... The implementation of intelligent technology in agriculture is seriously investigated as a way to increase agriculture production while reducing the amount of human labor. In agriculture, recent technology has seen image annotation utilizing deep learning techniques. Due to the rapid development of image data, image annotation has gained a lot of attention. The use of deep learning in image annota ...
DOI:
10.3390/agriculture12071033

15. Prediction of Potassium in Peach Leaves Using Hyperspectral Imaging and Multivariate Analysis

Author:
Megan Io Ariadne Abenina; Joe Mari Maja; Matthew Cutulle; Juan Carlos Melgar; Haibo Liu
Source:
AgriEngineering 2022 v.4 no.2 pp. 400-413
ISSN:
2624-7402
Subject:
disease detection,   etc   ; cultivars; least squares; leaves; models; peaches; pests; potassium; prediction; principal component analysis;     Show all 10 Subjects
Abstract:
... Hyperspectral imaging (HSI) is an emerging technology being utilized in agriculture. This system could be used to monitor the overall health of plants or in pest/disease detection. As sensing technology advancement expands, measuring nutrient levels and disease detection also progresses. This study aimed to predict three different levels of potassium (K) concentration in peach leaves using princip ...
DOI:
10.3390/agriengineering4020027

16. Deep multi-scale dual-channel convolutional neural network for Internet of Things apple disease detection

Author:
Wenzhuo Zhang; Guoxiong Zhou; Aibin Chen; Yahui Hu
Source:
Computers and electronics in agriculture 2022 v.194 pp. 106749
ISSN:
0168-1699
Subject:
disease detection,   etc   ; Internet; agriculture; apples; cameras; color; databases; electronics; neural networks; solar radiation; texture;     Show all 11 Subjects
Abstract:
... It is difficult to identify similar apples diseases due to the complicated changes in color and texture of diseased parts. In order to solve this problem, an Internet of Things (IoT) system for apple disease detection based on deep multi-scale dual-channel convolutional neural network (DMCNN) was proposed in this paper. Firstly, the image was transformed into HSV and RGB color subspaces through co ...
DOI:
10.1016/j.compag.2022.106749

17. ResTS: Residual Deep interpretable architecture for plant disease detection

Author:
Dhruvil Shah; Vishvesh Trivedi; Vinay Sheth; Aakash Shah; Uttam Chauhan
Source:
Information processing in agriculture 2022 v.9 no.2 pp. 212-223
ISSN:
2214-3173
Subject:
disease detection,   etc   ; agriculture; computer vision; crops; data collection; disease diagnosis; information; neural networks; teachers;     Show all 9 Subjects
Abstract:
... Recently many methods have been induced for plant disease detection by the influence of Deep Neural Networks in Computer Vision. However, the dearth of transparency in these types of research makes their acquisition in the real-world scenario less approving. We propose an architecture named ResTS (Residual Teacher/Student) that can be used as visualization and a classification technique for diagno ...
DOI:
10.1016/j.inpa.2021.06.001

18. Case-control study of behavior data from automated milk feeders in healthy or diseased dairy calves

Author:
Jannelle L. Morrison; Charlotte B. Winder; Catalina Medrano-Galarza; Pauline Denis; Derek Haley; Stephen J. LeBlanc; Joao Costa; Michael Steele; David L. Renaud
Source:
JDS communications 2022 v.3 no.3 pp. 201-206
ISSN:
2666-9102
Subject:
disease detection,   etc   ; automation; case-control studies; dairy industry; milk; milk consumption; milk replacer; risk; Ontario;     Show all 9 Subjects
Abstract:
... Group housing of preweaning dairy calves is increasing in popularity throughout the dairy industry. However, it can be more difficult to individually monitor calves to identify disease in these group systems. Automated milk feeders (AMF) not only provide producers with the opportunity to increase the milk allowance offered to preweaning calves but they can also monitor individual feeding behaviors ...
DOI:
10.3168/jdsc.2021-0153

19. Multifunctional amino acids empowering bifunctional biosensing platform for depression study

Author:
Shengnan Yang; Wei Feng; Lan Xue; Mengai Yin; Binshuai Li; Lina Lu; Fuju Dai; Jun Jiao; Qiang Chen
Source:
Biosensors & bioelectronics 2022 v.201 pp. 113972
ISSN:
0956-5663
Subject:
disease detection,   etc   ; biomarkers; biosensors; detection limit; electrochemistry; fluoxetine; glucocorticoid receptors; graphene oxide; hippocampus; nanocomposites; nanogold;     Show all 11 Subjects
Abstract:
... Poor availability of objective approaches hinders effective diagnosis and treatment for depression. Biosensors provide a promising platform for the development of quantitative and practical methods for disease detection, as well as for drug discovery. Here, we developed an electrochemical biosensor has been established with the ability to simply and accurately detect the trace glucocorticoid recep ...
DOI:
10.1016/j.bios.2022.113972

20. Data analysis supports monitoring and surveillance of sheep health and welfare in the Netherlands

Author:
M. van der Heijden; E. Dijkstra; M. Holstege; R. van den Brom; P. Vellema
Source:
Small ruminant research 2022 pp. 106831
ISSN:
0921-4488
Subject:
disease detection,   etc   ; census data; disease surveillance; flocks; monitoring; mortality; necropsy; notifiable disease; research; sheep; Netherlands;     Show all 11 Subjects
Abstract:
... Monitoring and surveillance of sheep health and welfare are of major importance for early detection of disease outbreaks. As in other European countries, there is a national notifiable disease surveillance system in the Netherlands. Additionally, Royal GD implemented a voluntary monitoring and surveillance system for sheep in 2003 which is built on a consultancy helpdesk, diagnostic testing includ ...
DOI:
10.1016/j.smallrumres.2022.106831