Article
Environmental Sciences
Anting Guo, Wenjiang Huang, Yingying Dong, Huichun Ye, Huiqin Ma, Bo Liu, Wenbin Wu, Yu Ren, Chao Ruan, Yun Geng
Summary: This study utilized UAV-based hyperspectral images to monitor yellow rust disease at the field scale, and found that the VI-TF-based models had the highest accuracy in each infection period, outperforming other models. Spatial resolution significantly influenced the monitoring accuracy of TF-based models, while having a negligible impact on VI-based monitoring accuracy. The optimal spatial resolution for monitoring yellow rust using the VI-TF-based model in each infection period was found to be 10 cm.
Article
Agronomy
Anton Terentev, Vladimir Badenko, Ekaterina Shaydayuk, Dmitriy Emelyanov, Danila Eremenko, Dmitriy Klabukov, Alexander Fedotov, Viktor Dolzhenko
Summary: Early crop disease detection is crucial for plant protection. This study aimed to explore the potential of hyperspectral remote sensing in early detection of wheat leaf rust. The research involved choosing tools for processing and analyzing hyperspectral remote sensing data, analyzing wheat leaf biochemical profile using chromatographic and spectrophotometric methods, and examining the relationship between hyperspectral remote sensing data and biochemical analysis results. The interdisciplinary approach utilized hyperspectral remote sensing, data processing methods, spectrophotometric and chromatographic methods. Findings revealed a strong correlation between VIS-NIR spectrometry data analysis and hyperspectral remote sensing data, and identified key wavebands (502, 466, 598, 718, 534, 766, 694, 650, 866, 602, 858 nm) for disease identification. SVM achieved an early disease detection accuracy of 97-100% from the fourth day after inoculation (dai).
Article
Chemistry, Analytical
Uferah Shafi, Rafia Mumtaz, Ihsan Ul Haq, Maryam Hafeez, Naveed Iqbal, Arslan Shaukat, Syed Mohammad Hassan Zaidi, Zahid Mahmood
Summary: This article presents a framework for classifying wheat yellow rust infection types using machine learning techniques. By collecting image datasets and extracting texture features, different algorithms were employed for classification, with CatBoost performing the best in terms of accuracy.
Article
Plant Sciences
Jingang Wang, Tian Tian, Haijiang Wang, Jing Cui, Xiaoyan Shi, Jianghui Song, Tiansheng Li, Weidi Li, Mingtao Zhong, Wenxu Zhang
Summary: Soil salinization poses a challenge to crop production in arid areas, but spectral analysis and remote sensing technology can assist in assessing the impact of salinity stress on crop photosynthesis.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Swarnajyoti Patra, Barnali Barman
Summary: A novel feature selection technique based on rough set theory is proposed in this work to reduce the dimensionality of hyperspectral images. The technique defines a new criterion by combining relevance and significance measures, and adopts a first order incremental search to select the most informative bands, showing better results compared to existing techniques. The proposed dependency measure definition is completely parameter free and computationally very cheap.
APPLIED SOFT COMPUTING
(2021)
Article
Chemistry, Analytical
Changchun Li, Yilin Wang, Chunyan Ma, Fan Ding, Yacong Li, Weinan Chen, Jingbo Li, Zhen Xiao
Summary: Leaf area index (LAI) estimation for winter wheat was studied using fractional order differential and continuous wavelet transform on canopy hyperspectral reflectance data. Models were constructed for different growth stages and the best prediction performance was found at the flowering and filling stages. This study provides technical reference for crop LAI estimation based on remote sensing technology.
Article
Plant Sciences
Elena Gultyaeva, Ekaterina Shaydayuk
Summary: The significance of yellow rust caused by Puccinia striiformis (Pst) has increased worldwide, including in Russia. The study aimed to explore the yellow rust resistance potential of modern common winter wheat cultivars included in the Russian Register of Breeding Achievements. The research found that some cultivars had multiple resistance genes, which can enhance genetic diversity and overall yellow rust resistance.
Article
Plant Sciences
Zi-Heng Feng, Lu-Yuan Wang, Zhe-Qing Yang, Yan-Yan Zhang, Xiao Li, Li Song, Li He, Jian-Zhao Duan, Wei Feng
Summary: The study optimized the monitoring model for wheat powdery mildew by processing canopy spectral data, using different algorithms and models. It provided new ideas and methods for realizing high-precision remote sensing monitoring of crop disease status.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Computer Science, Information Systems
Uferah Shafi, Rafia Mumtaz, Muhammad Deedahwar Mazhar Qureshi, Zahid Mahmood, Sikander Khan Tanveer, Ihsan Ul Haq, Syed Mohammad Hassan Zaidi
Summary: This research proposes a system to detect wheat rust disease and classify its infection types. Deep learning classifiers are used to identify the severity of rust disease, and an intelligent edge computing device is developed for disease monitoring. The aim of this research is to assist the agricultural community in employing preventive measures based on accurate diagnosis to improve wheat quality and production.
Article
Computer Science, Hardware & Architecture
Songlin Jin, Weidong Zhang, Pengfei Yang, Ying Zheng, Jinliang An, Ziyang Zhang, Peixin Qu, Xipeng Pan
Summary: By proposing a spatial-spectral feature extraction method to identify seeds, our research demonstrates that this method can classify hyperspectral images quickly, accurately, and nondestructively, achieving higher classification accuracy compared to other methods.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Automation & Control Systems
Jinya Su, Dewei Yi, Baofeng Su, Zhiwen Mi, Cunjia Liu, Xiaoping Hu, Xiangming Xu, Lei Guo, Wen-Hua Chen
Summary: This article explores the use of aerial visual perception for monitoring yellow rust disease, integrating state-of-the-art techniques such as multispectral imaging and deep learning U-Net. The developed framework shows improved performance in disease monitoring by extracting spectral-spatial information simultaneously, surpassing the classical spectral-based classifier (random forest algorithm).
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Agronomy
Changchun Li, Zhen Xiao, Yanghua Liu, Xiaopeng Meng, Xinyan Li, Xin Wang, Yafeng Li, Chenyi Zhao, Lipeng Ren, Chen Yang, Yinghua Jiao
Summary: This study used hyperspectral and leaf water content (LWC) data of winter wheat in 2020 and 2021 to estimate LWC during different growth periods. The hyperspectral data was transformed and processed using fractional order differential and continuous wavelet transform. The results showed that the fractional differential and continuous wavelet transform improved the correlation between spectral characteristics and LWC. The estimation accuracy was highest during the flowering period, especially when using mixed variables. The use of artificial neural network (ANN) model achieved the highest estimation accuracy. The outcomes of this study have the potential to provide new ideas for crop water monitoring.
Article
Geochemistry & Geophysics
Wei Wei, Songzheng Xu, Lei Zhang, Jinyang Zhang, Yanning Zhang
Summary: This research proposes a novel deep learning network that utilizes both labeled and unlabeled data for training, aiming to address overfitting caused by inaccurate labels in hyperspectral image classification. By exploiting the unsupervised structure knowledge in unlabeled data, the proposed method improves the accuracy of conventional supervised classification.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Chemistry, Multidisciplinary
Zhihui Li, Xin Fang, Tong Zhen, Yuhua Zhu
Summary: Wheat production safety is threatened by worldwide wheat yellow rust disease, which is difficult to detect in the early stage but manifests obvious symptoms in the middle and late stages. To address this issue, an optimized GhostNetV2 approach is proposed, which improves the training time, accuracy, and speed of disease identification compared to other lightweight model algorithms.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Electrical & Electronic
Tianxiang Zhang, Zhifang Yang, Zhiyong Xu, Jiangyun Li
Summary: This paper investigates the detection of wheat yellow rust severity and proposes a real-time detection algorithm based on UAV multispectral images and deep learning networks. The algorithm achieves a lightweight structure through a pruning strategy and enhances the network's ability with a Sparse Channel Attention module. Experimental results show that the proposed algorithm can accurately detect different levels of yellow rust with a reduced computation load.
IEEE SENSORS JOURNAL
(2022)
Article
Forestry
Rafael M. Navarro-Cerrillo, Pablo Gonzalez-Moreno, Francisco Jose Ruiz-Gomez, Rafael Sanchez-Cuesta, Antonio Gazol, J. Julio Camarero
Summary: The study analyzed the ecological issues of endangered and threatened Abies pinsapo forests in Andalusia, southern Spain, and found that under the pressure of climate and pests, tree defoliation and mortality rates increased. These issues are mainly influenced by the eastern region, with severe drought and pest threats.
FOREST ECOLOGY AND MANAGEMENT
(2022)
Article
Biochemistry & Molecular Biology
Giovanni Vimercati, Anna F. Probert, Lara Volery, Ruben Bernardo-Madrid, Sandro Bertolino, Vanessa Cespedes, Franz Essl, Thomas Evans, Belinda Gallardo, Laure Gallien, Pablo Gonzalez-Moreno, Marie Charlotte Grange, Cang Hui, Jonathan M. Jeschke, Stelios Katsanevakis, Ingolf Kuehn, Sabrina Kumschick, Jan Pergl, Petr Pysek, Loren Rieseberg, Tamara B. Robinson, Wolf-Christian Saul, Cascade J. B. Sorte, Montserrat Vila, John R. U. Wilson, Sven Bacher
Summary: This article introduces the IUCN Environmental Impact Classification for Alien Taxa (EICAT) and proposes EICAT+ system to assess both negative and positive impacts of alien species on native biodiversity. EICAT+ fills the gap in classifying positive impacts and provides information for understanding the consequences of biological invasions and conservation decisions.
Article
Environmental Sciences
Angel Cunill Camprubi, Pablo Gonzalez-Moreno, Victor Resco de Dios
Summary: In this study, we utilized random forests model to estimate live fuel moisture content at the subcontinental scale in the Mediterranean basin. We employed multiple predictors including MODIS spectral bands, vegetation indices, surface temperature, and the day of year. The RF model demonstrated lower root mean square errors compared to current approaches based on radiative transfer models, thus improving the accuracy of LFMC estimation.
Article
Agronomy
Antonio Jesus Ariza Salamanca, Rafael Ma Navarro-Cerrillo, Jayne Crozier, Clare Stirling, Pablo Gonzalez-Moreno
Summary: Establishment of a tree canopy in Cocoa Agroforestry Systems (C-AFS) provides higher carbon stocks and other ecosystem services. This study combines growth models and allometric equations to forecast carbon sequestration in a C-AFS trial in Cote d'Ivoire. The results suggest that timber trees store more than 45% of aboveground carbon stocks.
AGROFORESTRY SYSTEMS
(2022)
Article
Forestry
Laura Blanco-Cano, Rafael Maria Navarro-Cerrillo, Pablo Gonzalez-Moreno
Summary: Climate change affects species habitat, especially vulnerable species. This study using Bayesian approach and niche overlap metric methods, investigated the interactions between the endangered Abies pinsapo and competing species, revealing temperature and precipitation as key factors shaping the distribution of A. pinsapo, with vulnerable populations at low elevations.
FOREST ECOLOGY AND MANAGEMENT
(2022)
Article
Biodiversity Conservation
Ruben Bernardo-Madrid, Pablo Gonzalez-Moreno, Belinda Gallardo, Sven Bacher, Montserrat Vila
Summary: This study quantified and compared the consistency of protocol question scores in impact assessments of 60 terrestrial, freshwater and marine organisms, revealing that the majority of assessments showed high consistency, with some showing low consistency. Consistency was related to impact types and protocols used, suggesting room for improvement in repeatability.
Article
Forestry
Rafael Sanchez-Cuesta, Pablo Gonzalez-Moreno, Andres Cortes-Marquez, Rafael M. Navarro-Cerrillo, Francisco Jose Ruiz-Gomez
Summary: The decline and mortality of Quercus species worldwide are influenced by various factors, including the biotic agent Phytophthora cinnamomi. However, there is limited research on the interaction between P. cinnamomi and environmental factors, as well as the effects of environmental drivers on the host-pathogen system. This study examines the influence of soil and topography on the disease status of Quercus ilex and Q. suber plantations, and highlights the importance of mixed afforestation and the characterization of soil and topography at a precise scale to prevent afforestation failure.
Letter
Biodiversity Conservation
Wayne Dawson, Jodey M. Peyton, Oliver L. Pescott, Tim Adriaens, Elizabeth J. Cottier-Cook, Danielle S. Frohlich, Gillian Key, Chris Malumphy, Angeliki F. Martinou, Dan Minchin, Niall Moore, Wolfgang Rabitsch, Stephanie L. Rorke, Elena Tricarico, Katharine M. A. Turvey, Ian J. Winfield, David K. A. Barnes, Diane Baum, Keith Bensusan, Frederic J. Burton, Peter Carr, Peter Convey, Alison I. Copeland, Darren A. Fa, Liza Fowler, Emili Garcia-Berthou, Albert Gonzalez, Pablo Gonzalez-Moreno, Alan Gray, Richard W. Griffiths, Rhian Guillem, Antenor N. Guzman, Jane Haakonsson, Kevin A. Hughes, Ross James, Leslie Linares, Norbert Maczey, Stuart Mailer, Bryan Naqqi Manco, Stephanie Martin, Andrea Monaco, David G. Moverley, Christine Rose-Smyth, Jonathan Shanklin, Natasha Stevens, Alan J. Stewart, Alexander G. C. Vaux, Stephen J. Warr, Victoria Werenkaut, Helen E. Roy
Summary: Invasive non-native species pose a significant threat to island biodiversity, ecosystems, and economies. Preventing the introduction of high-risk species is the most cost-effective approach to mitigate their adverse impacts. A horizon scanning approach identified high-risk species and pathways in the United Kingdom Overseas Territories, providing guidance for biosecurity and surveillance efforts aimed at preventing future incursions.
CONSERVATION LETTERS
(2023)
Article
Physiology
Hongmei Li, Jingquan Zhu, Yumeng Cheng, Fuyan Zhuo, Yinmin Liu, Jingfeng Huang, Bryony Taylor, Belinda Luke, Meizhi Wang, Pablo Gonzalez-Moreno
Summary: This study aims to understand the behavioral patterns of different stages of locusts and identify the environmental factors modulating their body temperature under natural conditions. The results showed that locusts preferred the ground and reed canopy as their main activity subhabitats, with adults showing specific peaks of activity. Locusts' body temperature increased with development stage and size during the day, while the opposite pattern occurred at night. Therefore, biopesticides should be applied to younger locusts with lower body temperatures in the morning or at dusk.
FRONTIERS IN PHYSIOLOGY
(2023)
Article
Biodiversity Conservation
Ana Montero-Castano, Marcelo A. Aizen, Pablo Gonzalez-Moreno, Laura Cavallero, Montserrat Vila, Carolina L. Morales
Summary: Upon arrival to a new area, alien species have to overcome a series of barriers to survive, reproduce, and spread along the invasion continuum. Failing to understand the role of different barriers and factors across the invasion stages limit our ability to predict invasion dynamics. In this study, we investigate how the European plant Cytisus scoparius overcomes survival and reproductive barriers in Nahuel Huapi National Park, Argentina, by evaluating the influence of climatic and landscape factors, species traits, and their interaction with patch cover, plant height, and pollinator visitation rates.
BIOLOGICAL INVASIONS
(2023)
Article
Pharmacology & Pharmacy
David Campany-Herrero, Alba Pau-Parra, Pablo Gonzalez-Moreno, Jaume Vima-Bofarull, Danae Anguita-Domingo, Bruno Montoro-Ronsano
Summary: This retrospective study evaluated the relationship between ertapenem blood concentration and the risk of neurotoxicity. The results indicated that determining the plasma concentration of ertapenem may help to minimize the risk of neurological adverse events.
BRITISH JOURNAL OF CLINICAL PHARMACOLOGY
(2023)
Article
Environmental Sciences
Linsheng Huang, Xinyu Chen, Yingying Dong, Wenjiang Huang, Huiqin Ma, Hansu Zhang, Yunlei Xu, Jing Wang
Summary: This study evaluates the environmental suitability of wheat stripe rust in China using species distribution models, combining data from various disciplinary fields. Results show that meteorological factors, especially temperature and precipitation, have the greatest impact on the occurrence of stripe rust. This study provides a scientific basis for optimizing and improving the comprehensive management strategy of stripe rust.
Article
Chemistry, Multidisciplinary
Alex Quimis J. Gomez, Carlos A. Rivas, Pablo Gonzalez-Moreno, Rafael M. Navarro-Cerrillo
Summary: In many tropical regions, national forest plantation programs have led to habitat changes, but the effects on habitat fragmentation and landscape connectivity are not well understood.
APPLIED SCIENCES-BASEL
(2023)
Article
Environmental Sciences
Longlong Zhao, Hongzhong Li, Wenjiang Huang, Yingying Dong, Yun Geng, Huiqin Ma, Jinsong Chen
Summary: Locust plagues cause severe agricultural damage, and climate change-induced extreme events have expanded locust habitats. In this study, we analyzed how drought-flood dynamics and temperature affect locust habitats, reproduction, and aggregation using satellite imagery and meteorological products. Our findings provide insights into the outbreak mechanisms of locust plagues and propose an approach for identifying potential high-risk locust areas.
Proceedings Paper
Computer Science, Artificial Intelligence
David Guijo-Rubio, Victor M. Vargas, Javier Barbero-Gomez, Jose Die, Pablo Gonzalez-Moreno
Summary: Programming is becoming increasingly important in areas such as Life Sciences, and students need to improve their programming skills for data analysis. By using hackathon and teamwork-based tools, students from different disciplines successfully solved problems in the field of Life Sciences, creating a multidisciplinary learning experience that was highly rewarding for both students and faculty members.
INTERNATIONAL JOINT CONFERENCE 15TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE IN SECURITY FOR INFORMATION SYSTEMS (CISIS 2022) 13TH INTERNATIONAL CONFERENCE ON EUROPEAN TRANSNATIONAL EDUCATION (ICEUTE 2022)
(2023)
