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Journal articles on the topic 'Plant Canopies Monitoring'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Osawa, Akira. "Plant canopies: Their growth, form and function." Forest Ecology and Management 49, no. 1-2 (1992): 168–70. http://dx.doi.org/10.1016/0378-1127(92)90169-a.

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Paturkar, Abhipray, Gourab Sen Gupta, and Donald Bailey. "Making Use of 3D Models for Plant Physiognomic Analysis: A Review." Remote Sensing 13, no. 11 (2021): 2232. http://dx.doi.org/10.3390/rs13112232.

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Use of 3D sensors in plant phenotyping has increased in the last few years. Various image acquisition, 3D representations, 3D model processing and analysis techniques exist to help the researchers. However, a review of approaches, algorithms, and techniques used for 3D plant physiognomic analysis is lacking. In this paper, we investigate the techniques and algorithms used at various stages of processing and analysing 3D models of plants, and identify their current limiting factors. This review will serve potential users as well as new researchers in this field. The focus is on exploring studie

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Wen, Yibo, Linlan Zhuang, Hezhi Wang, Tongxin Hu, and Wenyi Fan. "An Automated Hemispherical Scanner for Monitoring the Leaf Area Index of Forest Canopies." Forests 13, no. 9 (2022): 1355. http://dx.doi.org/10.3390/f13091355.

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The leaf area index (LAI) is an important structural parameter of plant canopies used in terrestrial biosphere models. Optical methods are commonly used for measuring LAI due to their non-destructive nature, convenience, and rapidity. In the present study, a novel instrument, named the Automated Hemispherical Scanner (AHS), was developed to measure plant area index (PAI) for monitoring daily changes in LAI in forest ecosystems. In the AHS, an optical sensor driven by a pair of servomotors is used to observe hemispherical light transmission continuously at adjustable intervals, and a blue filte

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Bagley, Stuart A., Jonathan A. Atkinson, Henry Hunt, Michael H. Wilson, Tony P. Pridmore, and Darren M. Wells. "Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping." Sensors 20, no. 11 (2020): 3319. http://dx.doi.org/10.3390/s20113319.

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High-throughput plant phenotyping in controlled environments (growth chambers and glasshouses) is often delivered via large, expensive installations, leading to limited access and the increased relevance of “affordable phenotyping” solutions. We present two robot vectors for automated plant phenotyping under controlled conditions. Using 3D-printed components and readily-available hardware and electronic components, these designs are inexpensive, flexible and easily modified to multiple tasks. We present a design for a thermal imaging robot for high-precision time-lapse imaging of canopies and

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Xu, Zuo, and Dalong Jiang. "AI-Powered Plant Science: Transforming Forestry Monitoring, Disease Prediction, and Climate Adaptation." Plants 14, no. 11 (2025): 1626. https://doi.org/10.3390/plants14111626.

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The integration of artificial intelligence (AI) and forestry is driving transformative advances in precision monitoring, disaster management, carbon sequestration, and biodiversity conservation. However, significant knowledge gaps persist in cross-ecological model generalisation, multi-source data fusion, and ethical implementation. This review provides a comprehensive overview of AI’s transformative role in forestry, focusing on three key areas: resource monitoring, disaster management, and sustainability. Data were collected via a comprehensive literature search of academic databases from 20

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Zhao, Yibo, Shaogang Lei, Xiaotong Han, et al. "Research on the Inversion Method of Dust Content on Mining Area Plant Canopies Based on UAV-Borne VNIR Hyperspectral Data." Drones 9, no. 4 (2025): 256. https://doi.org/10.3390/drones9040256.

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Monitoring dust on plant canopies around open-pit coal mines is crucial to assessing environmental pollution and developing effective dust suppression strategies. This research focuses on the Ha’erwusu open-pit coal mine in Inner Mongolia, China, using measured dust content on plant canopies and UAV-borne VNIR hyperspectral data as the data sources. The study employed five spectral transformation forms—first derivative (FD), second derivative (SD), logarithm transformation (LT), reciprocal transformation (RT), and square root (SR)—alongside the competitive adaptive reweighted sampling (CARS) m

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Merrick, Trina, Ralf Bennartz, Maria Luisa S. P. Jorge, Stephanie Pau, and John Rausch. "Evaluation of Plant Stress Monitoring Capabilities Using a Portable Spectrometer and Blue-Red Grow Light." Sensors 22, no. 9 (2022): 3411. http://dx.doi.org/10.3390/s22093411.

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Remote sensing offers a non-destructive method to detect plant physiological response to the environment by measuring chlorophyll fluorescence (CF). Most methods to estimate CF require relatively complex retrieval, spectral fitting, or modelling methods. An investigation was undertaken to evaluate measurements of CF using a relatively straightforward technique to detect and monitor plant stress with a spectroradiometer and blue-red light emitting diode (LED). CF spectral response of tomato plants treated with a photosystem inhibitor were assessed and compared to traditional reflectance-based i

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Comella, Laura Maria, Florian Bregler, Eiko Hager, et al. "Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks." Sensors 22, no. 13 (2022): 5048. http://dx.doi.org/10.3390/s22135048.

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The leaf area index (LAI) is a key parameter in the context of monitoring the development of tree crowns and plants in general. As parameters such as carbon assimilation, environmental stress on carbon, and the water fluxes within tree canopies are correlated to the leaves surface, this parameter is essential for understanding and modeling ecological processes. However, its continuous monitoring using manual state-of-the-art measurement instruments is still challenging. To address this challenge, we present an innovative sensor concept to obtain the LAI based on the cheap and easy to integrate

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Zhao, Yibo, and Shaogang Lei. "Research on the Inversion Method of Dust Retention in Grassland Plant Canopies Based on UAV-Borne Hyperspectral Data." Land 14, no. 3 (2025): 458. https://doi.org/10.3390/land14030458.

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Monitoring the dust retention content in grassland plants around open-pit coal mines is of significant importance for environmental pollution monitoring and the development of dust control strategies. This paper focuses on the HulunBuir grassland in the Inner Mongolia Autonomous Region, China. UAV-borne hyperspectral data and measured dust retention content in plant canopies are used as data sources. The spectral response characteristics of canopy dust retention are analyzed, and four types of optimized spectral indices are constructed, including the difference index (DI), ratio index (RI), no

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Clarke, Thomas R., and M. Susan Moran. "Monitoring Crop Water Status and Irrigation Needs Using Multispectral Airborne Sensors." HortScience 30, no. 4 (1995): 905D—905. http://dx.doi.org/10.21273/hortsci.30.4.905d.

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Water application efficiency can be improved by directly monitoring plant water status rather than depending on soil moisture measurements or modeled ET estimates. Plants receiving sufficient water through their roots have cooler leaves than those that are water-stressed, leading to the development of the Crop Water Stress Index based on hand-held infrared thermometry. Substantial error can occur in partial canopies, however, as exposed hot soil contributes to deceptively warm temperature readings. Mathematically comparing red and near-infrared reflectances provides a measure of vegetative cov

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Henshall, W. R., R. M. Beresford, R. W. Chynoweth, and P. Ramankutty. "Comparing surface wetness inside and outside grape canopies for regionwide assessment of plant disease risk." New Zealand Plant Protection 58 (August 1, 2005): 80–83. http://dx.doi.org/10.30843/nzpp.2005.58.4258.

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Wetness duration measured by flat plate sensors inside and outside a grape canopy was recorded from DecemberMarch Sensors outside the canopy generally recorded longer wetness duration than sensors inside the canopy For days with rain short wetness durations detected by outside sensors were not detected by inside sensors because of sheltering by the canopy When wetness arose solely from dew duration inside was much shorter than outside for prolonged wet periods Wetness was used to calculate infection periods according to two botrytis bunch rot risk models Agreement between sensors was worse ins

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Gousset, Silvère, Cédric Legout, Philippe Choler, Samuel Barnola, Laurent Longuevergne, and Didier Voisin. "Development and testing of a hyperspectral camera network to monitor plant canopies and sediment transport dynamics." ARPHA Conference Abstracts 8 (May 28, 2025): e152517. https://doi.org/10.3897/aca.8.e152517.

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There is growing interest in hyperspectral imaging to complement observation needs and techniques required to capture the critical zone dynamics. It is already widely used in remote sensing satellite imagery, for regional-scale monitoring of canopies (Asner et al. 2004), or suspended sediment transport (Yepez et al. 2017). Spectral imaging offers dense, remote and non-intrusive measurement coverage.Its implementation at fixed-station for fine temporal monitoring would ensure maximum temporal coverage to study the phenology and functioning of ecosystems (vegetation-water-soil interactions) and

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Ma, Hanyu, Weiliang Wen, Wenbo Gou, et al. "Three-Dimensional Time-Series Monitoring of Maize Canopy Structure Using Rail-Driven Plant Phenotyping Platform in Field." Agriculture 15, no. 1 (2024): 6. https://doi.org/10.3390/agriculture15010006.

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The spatial and temporal dynamics of crop canopy structure are influenced by cultivar, environment, and crop management practices. However, continuous and automatic monitoring of crop canopy structure is still challenging. A three-dimensional (3D) time-series phenotyping study of maize canopy was conducted using a rail-driven high-throughput plant phenotyping platform (HTPPP) in field conditions. An adaptive sliding window segmentation algorithm was proposed to obtain plots and rows from canopy point clouds. Maximum height (Hmax), mean height (Hmean), and canopy cover (CC) of each plot were ex

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Beadle, James, C. James Taylor, Kirsti Ashworth, and David Cheneler. "Plant Leaf Position Estimation with Computer Vision." Sensors 20, no. 20 (2020): 5933. http://dx.doi.org/10.3390/s20205933.

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Autonomous analysis of plants, such as for phenotyping and health monitoring etc., often requires the reliable identification and localization of single leaves, a task complicated by their complex and variable shape. Robotic sensor platforms commonly use depth sensors that rely on either infrared light or ultrasound, in addition to imaging. However, infrared methods have the disadvantage of being affected by the presence of ambient light, and ultrasound methods generally have too wide a field of view, making them ineffective for measuring complex and intricate structures. Alternatives may incl

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Gaffney, Rowan, Lauren Porensky, Feng Gao, et al. "Using APAR to Predict Aboveground Plant Productivity in Semi-Aid Rangelands: Spatial and Temporal Relationships Differ." Remote Sensing 10, no. 9 (2018): 1474. http://dx.doi.org/10.3390/rs10091474.

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Monitoring of aboveground net primary production (ANPP) is critical for effective management of rangeland ecosystems but is problematic due to the vast extent of rangelands globally, and the high costs of ground-based measurements. Remote sensing of absorbed photosynthetically active radiation (APAR) can be used to predict ANPP, potentially offering an alternative means of quantifying ANPP at both high temporal and spatial resolution across broad spatial extents. The relationship between ANPP and APAR has often been quantified based on either spatial variation across a broad region or temporal

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Lakso, Alan N., Michael Santiago, and Abraham D. Stroock. "Monitoring Stem Water Potential with an Embedded Microtensiometer to Inform Irrigation Scheduling in Fruit Crops." Horticulturae 8, no. 12 (2022): 1207. http://dx.doi.org/10.3390/horticulturae8121207.

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The water status of fruit and nut crops is critical to the high productivity, quality and value of these crops. Water status is often estimated and managed with indirect measurements of soil moisture and models of evapotranspiration. However, cultivated trees and vines have characteristics and associated cultural practices that complicate such methods, particularly variable discontinuous canopies, and extensive but low-density, variable root systems with relatively high hydraulic resistance. Direct and continuous measurement of plant water status is desirable in these crops as the plant integr

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Díaz-Delgado, Ricardo, Mizar Torrijo-Salesa, González Luis Alfonso Ramírez, et al. "Long-term monitoring of woody plants of Doñana shrublands (SW Spain) from 2008 to 2023." Biodiversity Data Journal 12 (December 11, 2024): e139074. https://doi.org/10.3897/BDJ.12.e139074.

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The long-term monitoring of the plant cover of Doñana shrublands is part of a harmonised protocol for the Long-term Ecological Monitoring Programme of Natural Resources and Processes targeting Terrestrial Vegetation. The general aim of this protocol is to monitor and assess the dynamics and trends of shrubland plant communities in Doñana. For shrublands, percentage cover is recorded annually, starting in 2008, by the Doñana Long-Term Monitoring Team in one field sampling campaign per year during the flowering season (between March and May) across 21 permanent square plots (15 m x 15 m). Perman

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Pereira, Rodrigo Moura, Derblai Casaroli, Lucas Melo Vellame, José Alves Júnior, and Adão Wagner Pêgo Evangelista. "Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI)." Pesquisa Agropecuária Tropical 46, no. 2 (2016): 140–48. http://dx.doi.org/10.1590/1983-40632016v4639303.

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ABSTRACT Large farmland areas and the knowledge on the interaction between solar radiation and vegetation canopies have increased the use of data from orbital remote sensors in sugarcane monitoring. However, the constituents of the atmosphere affect the reflectance values obtained by imaging sensors. This study aimed at improving a sugarcane Leaf Area Index (LAI) estimation model, concerning the Normalized Difference Vegetation Index (NDVI) subjected to atmospheric correction. The model generated by the NDVI with atmospheric correction showed the best results (R2 = 0.84; d = 0.95; MAE = 0.44;

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D'ONGHIA, Anna Maria, Franco SANTORO, Serena Anna MINUTILLO, et al. "Optimisation of sampling and testing for asymptomatic olive trees infected by Xylella fastidiosa in Apulia region, Italy." Phytopathologia Mediterranea 61, no. 3 (2022): 439–49. http://dx.doi.org/10.36253/phyto-13732.

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Early detection of Xylella fastidiosa outbreaks in Apulian olive groves is crucial, especially in buffer zones and pathogen-free areas where olive trees are asymptomatic. Three studies were conducted. Two were on the spatial and temporal progression of X. fastidiosa infections in tree canopies of asymptomatic or mildly symptomatic olive trees of tolerant (‘Leccino’) and susceptible (‘Cellina di Nardò’ and ‘Ogliarola salentina’) cultivars. Despite different trends in pathogen infection rates and concentrations between ‘Leccino’ and susceptible olive cultivars over the study period, results show

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Wilson, Lucy, Richard van Dongen, Saul Cowen, and Todd P. Robinson. "Mapping Restoration Activities on Dirk Hartog Island Using Remotely Piloted Aircraft Imagery." Remote Sensing 14, no. 6 (2022): 1402. http://dx.doi.org/10.3390/rs14061402.

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Conservation practitioners require cost-effective and repeatable remotely sensed data for assistive monitoring. This paper tests the ability of standard remotely piloted aircraft (DJI Phantom 4 Pro) imagery to discriminate between plant species in a rangeland environment. Flights were performed over two 0.3–0.4 ha exclusion plot sites, established as controls to protect vegetation from translocated animal disturbance on Dirk Hartog Island, Western Australia. Comparisons of discriminatory variables, classification potential, and optimal flight height were made between plot sites with different

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Wang, Yu, Chunhui Feng, Yiru Ma, et al. "Estimation of Nitrogen Concentration in Walnut Canopies in Southern Xinjiang Based on UAV Multispectral Images." Agronomy 13, no. 6 (2023): 1604. http://dx.doi.org/10.3390/agronomy13061604.

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Nitrogen is one of the most important nutrients affecting the growth and fruit quality of walnut trees. Rapid and accurate monitoring of nitrogen concentration in the walnut canopy can provide a digital basis for its nutritional diagnosis and precision fertilization. Consequently, the main purpose of this study was to use Unmanned Aerial Vehicle (UAV) remote sensing technology to monitor the nitrogen concentration of walnut canopies. In this study, UAV multispectral images of the canopies of nine walnut orchards with different management levels in Wensu County, South Xinjiang, China, were coll

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Saha, Kowshik Kumar, Nikos Tsoulias, Cornelia Weltzien, and Manuela Zude-Sasse. "Estimation of Vegetative Growth in Strawberry Plants Using Mobile LiDAR Laser Scanner." Horticulturae 8, no. 2 (2022): 90. http://dx.doi.org/10.3390/horticulturae8020090.

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Monitoring of plant vegetative growth can provide the basis for precise crop management. In this study, a 2D light detection and ranging (LiDAR) laser scanner, mounted on a linear conveyor, was used to acquire multi-temporal three-dimensional (3D) data from strawberry plants (‘Honeoye’ and ‘Malling Centenary’) 14–77 days after planting (DAP). Canopy geometrical variables, i.e., points per plant, height, ground projected area, and canopy volume profile, were extracted from 3D point cloud. The manually measured leaf area exhibited a linear relationship with LiDAR-derived parameters (R2 = 0.98, 0

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Asbani, Nur, Ronald H. Cherry, Julien M. Beuzelin, Hardev S. Sandhu, Oscar E. Liburd, and Gregg S. Nuessly. "Within-plant distribution and rapid assessment of sugarcane rust mite population on sugarcane canopy." Acarologia 64, no. 3 (2024): 733–44. http://dx.doi.org/10.24349/bk7t-z0f0.

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Sugarcane rust mite (SRM), Abacarus sacchari, has been recognized in Florida since 1983. However, no detection technique had been developed yet, whereas a reliable, effective, and efficient technique is important in a mite management practice. The purposes of this study were to determine the within-plant distribution and to develop a sampling technique for SRM. The study was carried out in sugarcane fields naturally infested with the mite population. The mite distribution was identified with the visual direct counting technique and the imprinting technique. Subsequently, the effectiveness and

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Detka, Jon, Hayley Coyle, Marcella Gomez, and Gregory S. Gilbert. "A Drone-Powered Deep Learning Methodology for High Precision Remote Sensing in California’s Coastal Shrubs." Drones 7, no. 7 (2023): 421. http://dx.doi.org/10.3390/drones7070421.

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Wildland conservation efforts require accurate maps of plant species distribution across large spatial scales. High-resolution species mapping is difficult in diverse, dense plant communities, where extensive ground-based surveys are labor-intensive and risk damaging sensitive flora. High-resolution satellite imagery is available at scales needed for plant community conservation across large areas, but can be cost prohibitive and lack resolution to identify species. Deep learning analysis of drone-based imagery can aid in accurate classification of plant species in these communities across lar

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Redfield, Garth W. "Atmospheric Deposition of Phosphorus to the Everglades: Concepts, Constraints, and Published Deposition Rates for Ecosystem Management." Scientific World JOURNAL 2 (2002): 1843–73. http://dx.doi.org/10.1100/tsw.2002.813.

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This paper summarizes concepts underlying the atmospheric input of phosphorus (P) to ecosystems, published rates of P deposition, measurement methods, and approaches to future monitoring and research. P conveyed through the atmosphere can be a significant nutrient source for some freshwater and marine ecosystems. Particle sources and sinks at the land-air interface produce variation in P deposition from the atmosphere across temporal and spatial scales. Natural plant canopies can affect deposition rates by changing the physical environment and surface area for particle deposition. Land-use pat

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Zheng, Hengbiao, Jifeng Ma, Meng Zhou, et al. "Enhancing the Nitrogen Signals of Rice Canopies across Critical Growth Stages through the Integration of Textural and Spectral Information from Unmanned Aerial Vehicle (UAV) Multispectral Imagery." Remote Sensing 12, no. 6 (2020): 957. http://dx.doi.org/10.3390/rs12060957.

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This paper evaluates the potential of integrating textural and spectral information from unmanned aerial vehicle (UAV)-based multispectral imagery for improving the quantification of nitrogen (N) status in rice crops. Vegetation indices (VIs), normalized difference texture indices (NDTIs), and their combination were used to estimate four N nutrition parameters leaf nitrogen concentration (LNC), leaf nitrogen accumulation (LNA), plant nitrogen concentration (PNC), and plant nitrogen accumulation (PNA). Results demonstrated that the normalized difference red-edge index (NDRE) performed best in e

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Blaikie, SJ, KB Kelly, WK Mason, and FM Martin. "Productivity of irrigated pastures following paraplowing and gypsum slotting of subsoil exposed by laser landforming dash a short term study." Australian Journal of Agricultural Research 39, no. 5 (1988): 837. http://dx.doi.org/10.1071/ar9880837.

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The effect of two soil amelioration techniques (paraplow and gypsum-enriched slots) on the productivity of white clover/ryegrass pasture was assessed by monitoring plant and soil water status and canopy gasexchange during an irrigation cycle. The soil was a dense clay, exposed when the topsoil was removed during laser landforming. Pasture growth on such exposed subsoils is very slow.All parameters of soil and plant water status indicated that there was some benefit from amelioration, with slots > paraplow > control. This trend was reflected in canopy photosynthesis. The photosynthetic ef

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Fieuzal, R., B. Duchemin, L. Jarlan, et al. "Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops." Hydrology and Earth System Sciences Discussions 7, no. 4 (2010): 6207–42. http://dx.doi.org/10.5194/hessd-7-6207-2010.

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Abstract. The objective of this study is to get a better understanding of radar signal over irrigated wheat fields and to assess the potentialities of radar observations for the monitoring of soil moisture. Emphasis is put on the use of high spatial and temporal resolution satellite data (ENVISAT/ASAR and FORMOSAT-2). Time series of images were collected over the Yaqui irrigated area (Mexico) throughout one agricultural season from December 2007 to May 2008, together with measurements of soil and vegetation characteristics and agricultural practices. The comprehensive analysis of these data in

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Wang, Rui, Qi Chen, and Dexiang Wang. "Effects of Altitude, Plant Communities, and Canopies on the Thermal Comfort, Negative Air Ions, and Airborne Particles of Mountain Forests in Summer." Sustainability 14, no. 7 (2022): 3882. http://dx.doi.org/10.3390/su14073882.

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Forest bathing is considered an economical, feasible, and sustainable way to solve human sub-health problems caused by urban environmental degradation and to promote physical and mental health. Mountain forests are ideal for providing forest baths because of their large area and ecological environment. The regulatory mechanism of a mountain forest plant community in a microenvironment conducive to forest bathing is the theoretical basis for promoting physical and mental health through forest bathing in mountain forests. Based on field investigations and measurements, differences in the daily u

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Kuester, Theres, and Daniel Spengler. "Structural and Spectral Analysis of Cereal Canopy Reflectance and Reflectance Anisotropy." Remote Sensing 10, no. 11 (2018): 1767. http://dx.doi.org/10.3390/rs10111767.

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The monitoring of agricultural areas is one of the most important topics for remote sensing data analysis, especially to assist food security in the future. To improve the quality and quantify uncertainties, it is of high relevance to understand the spectral reflectivity regarding the structural and spectral properties of the canopy. The importance of understanding the influence of plant and canopy structure is well established, but, due to the difficulty of acquiring reflectance data from numerous differently structured canopies, there is still a need to study the structural and spectral depe

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Salvatori, Leonardo, Marco Cervellini, Stefano Chelli, et al. "Investigating the temporal Alpha, Beta and Gamma plant diversity on 22 years monitoring approach at the LTER site "Montagna di Torricchio" (Central Apennines, Italy)." ARPHA Conference Abstracts 8 (May 28, 2025): e155592. https://doi.org/10.3897/aca.8.e155592.

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Ecological monitoring recently acquired importance given the current global changes and the human impact on ecosystems. Most of research focus on investigating variation in species diversity with short-term collections of data. Other scholars use long-term data but based on resurveys with two distinct points in time. In this work, we present a different approach dealing with temporal variation of plant communities in term of alpha, beta and gamma diversity.Data belongs to a dataset published on the journal "Data in Brief" as a data article and available on the repository "b2Share" (https://doi

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Fieuzal, R., B. Duchemin, L. Jarlan, et al. "Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops." Hydrology and Earth System Sciences 15, no. 4 (2011): 1117–29. http://dx.doi.org/10.5194/hess-15-1117-2011.

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Abstract. The objective of this study is to get a better understanding of radar signal over irrigated wheat fields and to assess the potentialities of radar observations for the monitoring of soil moisture. Emphasis is put on the use of high spatial and temporal resolution satellite data (Envisat/ASAR and Formosat-2). Time series of images were collected over the Yaqui irrigated area (Mexico) throughout one agricultural season from December 2007 to May 2008, together with measurements of soil and vegetation characteristics and agricultural practices. The comprehensive analysis of these data in

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Martelli, Roberta, Vincenzo Civitarese, Lorenzo Barbanti, et al. "Multi-Parametric Approach to Management Zone Delineation in a Hazelnut Grove in Italy." Sustainability 15, no. 13 (2023): 10106. http://dx.doi.org/10.3390/su151310106.

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The increase in high-density hazelnut (Corylus avellana) areas drives the interest in practices of precision management. This work addressed soil apparent electrical conductivity (ECa), RGB aerial (UAV) images, proximal sensing, and field scouting in delineating and validating management zones (MZs) in a 2.96 ha hazelnut grove in Italy. ECa data were fitted to a semi-variogram, interpolated (simple kriging), and clustered, resulting in two MZs that were subjected to soil analysis. RGB imagery was used to extract tree canopies from the soil background and determine two vegetation indices (VIs)

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Maraveas, Chrysanthos. "Image Analysis Artificial Intelligence Technologies for Plant Phenotyping: Current State of the Art." AgriEngineering 6, no. 3 (2024): 3375–407. http://dx.doi.org/10.3390/agriengineering6030193.

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Modern agriculture is characterized by the use of smart technology and precision agriculture to monitor crops in real time. The technologies enhance total yields by identifying requirements based on environmental conditions. Plant phenotyping is used in solving problems of basic science and allows scientists to characterize crops and select the best genotypes for breeding, hence eliminating manual and laborious methods. Additionally, plant phenotyping is useful in solving problems such as identifying subtle differences or complex quantitative trait locus (QTL) mapping which are impossible to s

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Li, Penglei, Xiao Zhang, Wenhui Wang, et al. "Estimating aboveground and organ biomass of plant canopies across the entire season of rice growth with terrestrial laser scanning." International Journal of Applied Earth Observation and Geoinformation 91 (September 2020): 102132. http://dx.doi.org/10.1016/j.jag.2020.102132.

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Madurapperuma, Buddhika D., Peter G. Oduor, Mohammad J. Anar, and Larry A. Kotchman. "Understanding Factors that Correlate or Contribute to Exotic Russian-olive (Elaeagnus angustifolia) Invasion at a Wildland–Urban Interface Ecosystem." Invasive Plant Science and Management 6, no. 1 (2013): 130–39. http://dx.doi.org/10.1614/ipsm-d-12-00021.1.

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AbstractUnderstanding the ecological distribution range of exotic trees in an arboreal ecosystem is essential to managing natural forest resources sustainably. Forest resource mapping can be applied as a powerful tool in the identification of forest resource threat patterns, and in monitoring ongoing changes associated with a landscape. This study offers an insight on Russian-olive and its impact on a spatially bound ecosystem, namely, Bismarck–Mandan Wildland–Urban Interface (BMWUI). Data from the National Agricultural Imagery Program collected in 2005 and 2010 and in situ reference data were

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Zhang, Canting, Xicun Zhu, Meixuan Li, et al. "Utilization of the Fusion of Ground-Space Remote Sensing Data for Canopy Nitrogen Content Inversion in Apple Orchards." Horticulturae 9, no. 10 (2023): 1085. http://dx.doi.org/10.3390/horticulturae9101085.

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Utilizing multi-source remote sensing data fusion to achieve efficient and accurate monitoring of crop nitrogen content is crucial for precise crop management. In this study, an effective integrated method for inverting nitrogen content in apple orchard canopies was proposed based on the fusion of ground-space remote sensing data. Firstly, ground hyper-spectral data, unmanned aerial vehicles (UAVs) multi-spectral data, and apple leaf samples were collected from the apple tree canopy. Secondly, the canopy spectral information was extracted, and the hyper-spectral and UAV multi-spectral data wer

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Islam, Sumaiya, Samsuzzaman, Md Nasim Reza, et al. "Image Processing and Support Vector Machine (SVM) for Classifying Environmental Stress Symptoms of Pepper Seedlings Grown in a Plant Factory." Agronomy 14, no. 9 (2024): 2043. http://dx.doi.org/10.3390/agronomy14092043.

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Environmental factors such as temperature, humidity, light, and CO2 influence plant growth, and unfavorable environmental conditions cause stress in plants, producing symptoms in their early growth stages. The increasing importance of optimizing crop management strategies has led to a rising demand for the precise evaluation of stress symptoms during early plant growth. Advanced technologies are transforming plant health monitoring through enabling image-based stress analysis. Machine learning (ML) models can effectively identify the important features and morphological changes connected with

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Qian, Tingting, Xiuguo Zheng, Juan Yang, et al. "Optimal Utilization of Light Energy in Semiclosed Greenhouse Using Three-Dimensional Cucumber Model." Scientific Programming 2020 (August 1, 2020): 1–12. http://dx.doi.org/10.1155/2020/8855063.

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In the east of China, low temperature and light energy in winter are the main factors for the decline in cucumber yield, as well as in greenhouses without supplementary light. Optimal utilization of light energy is critical to increase cucumber yield. In this study, experimental measurements were conducted in two scenarios, April to May (Apr-May) and November to December (Nov-Dec) 2015, respectively, to analyze leaf development, dry matter accumulation, and yield of cultivated cucumber. Statistical analysis showed that leaves grew in Nov-Dec had larger leaf area and lower dry matter than leave

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Santos, Antonio Odair, Homero Bergamaschi, Marcel Fuchs, Luís Mauro G. Rosa, and João Ito Bergonci. "SUNLIT AND SHADED MAIZE CANOPY WATER LOSS UNDER VARIED WATER STRESS." Revista Brasileira de Engenharia Agrícola e Ambiental 3, no. 3 (1999): 261–67. http://dx.doi.org/10.1590/1807-1929/agriambi.v3n3p261-267.

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ABSTRACT The precise estimation of transpiration from plant canopies is important for the monitoring of crop water use and management of many agricultural operations related to water use planning. The aim of this study was to estimate transpiration from sunlit and shaded fractions of a maize ( Zea mays L.) canopy, using the Penman-Monteith energy balance equation with modifications introduced by Fuchs et al. (1987) and Fuchs & Cohen (1989). Estimated values were validated by a heat pulse system, which was used to measure stem sap flow and by a weighing lysimeter. A relationship between inc

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Southwick, S. M., K. Shackel, and J. T. Yeager. "087 RELATIONSHIP BETWEEN SUMMER TEMPERATURE AND DEEP SUTURE FORMATION IN `BING' SWEET CHERRY." HortScience 29, no. 5 (1994): 440d—440. http://dx.doi.org/10.21273/hortsci.29.5.440d.

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`Bing' sweet cherry is the most widely planted cultivar grown in the Western US because of widespread market acceptance. High prices are associated with early maturing `Bings' so growers are inclined to plant in early maturing growing regions. High numbers of less marketable, abnormally shaped (deep sutures, spurs, doubles) fruit tend to be produced in these regions. It is thought that abnormal fruit development is associated with high summer temperatures. Dataloggers equipped with thermocouples were located in 7 California cherry growing regions. Thermocouples were positioned throughout tree

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López-Sánchez, Aida, Sonia Roig, Rodolfo Dirzo, and Ramón Perea. "Effects of Domestic and Wild Ungulate Management on Young Oak Size and Architecture." Sustainability 13, no. 14 (2021): 7930. http://dx.doi.org/10.3390/su13147930.

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Scattered oaks in traditional silvopastoral systems (i.e., “dehesas”) provide important ecological services. However, livestock intensification applied to these systems over the last century has affected the architecture of young oak plants. This unsuitable rangeland management practice jeopardizes the long-term system sustainability. Here we examine the alterations in architecture of regenerating oak plants in Mediterranean dehesas under three representative management regimes: (1) traditional management with extensive sheep grazing; (2) commercially driven management with extensive cattle gr

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Manganiello, Gelsomina, Nicola Nicastro, Luciano Ortenzi, Federico Pallottino, Corrado Costa, and Catello Pane. "Trichoderma Biocontrol Performances against Baby-Lettuce Fusarium Wilt Surveyed by Hyperspectral Imaging-Based Machine Learning and Infrared Thermography." Agriculture 14, no. 2 (2024): 307. http://dx.doi.org/10.3390/agriculture14020307.

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Fusarium oxysporum f. sp. lactucae is one of the most aggressive baby-lettuce soilborne pathogens. The application of Trichoderma spp. as biocontrol agents can minimize fungicide treatments and their effective targeted use can be enhanced by support of digital technologies. In this work, two Trichoderma harzianum strains achieved 40–50% inhibition of pathogen radial growth in vitro. Their effectiveness in vivo was surveyed by assessing disease incidence and severity and acquiring hyperspectral and thermal features of the canopies being treated. Infected plants showed a reduced light absorption

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Xing, Naichen, Wenjiang Huang, Qiaoyun Xie, et al. "A Transformed Triangular Vegetation Index for Estimating Winter Wheat Leaf Area Index." Remote Sensing 12, no. 1 (2019): 16. http://dx.doi.org/10.3390/rs12010016.

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Leaf area index (LAI) is a key parameter in plant growth monitoring. For several decades, vegetation indices-based empirical method has been widely-accepted in LAI retrieval. A growing number of spectral indices have been proposed to tailor LAI estimations, however, saturation effect has long been an obstacle. In this paper, we classify the selected 14 vegetation indices into five groups according to their characteristics. In this study, we proposed a new index for LAI retrieval-transformed triangular vegetation index (TTVI), which replaces NIR and red bands of triangular vegetation index (TVI

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Clarke, Thomas R. "An Empirical Approach for Detecting Crop Water Stress Using Multispectral Airborne Sensors." HortTechnology 7, no. 1 (1997): 9–16. http://dx.doi.org/10.21273/horttech.7.1.9.

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Irrigation scheduling can be improved by directly monitoring plant water status rather than depending solely on soil water content measurements or modeled evapotranspiration estimates. Plants receiving sufficient water through their roots have cooler leaves than those that are water stressed, leading to the development of the crop water stress index, which uses hand-held infrared thermometers as tools for scheduling irrigations. However, substantial error can occur in partial canopies when a downward-pointing infrared thermometer measures leaf temperature and the temperature of exposed, hot so

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Di Girolamo, Paolo, Carmine Serio, Volker Wulfmeyer, Andreas Behrendt, and Davide Dionisi. "CO2 Profiling by Space-Borne Raman Lidar." EPJ Web of Conferences 237 (2020): 01004. http://dx.doi.org/10.1051/epjconf/202023701004.

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As clearly reported in the IPCC fifth Assessment Report, CO2 emissions are already producing destructive effects to the plant ecosystem through the alteration of soil-atmosphere interaction mechanisms. Although the space and ground network for CO2 monitoring has regularly expanded over the past 50 years, it does not guarantee the necessary spatial and temporal resolution needed for a quantitative analysis of sources and sinks. For the purpose of estimating forests’ carbon capturing capabilities, accurate measurements of CO2 gradients between the forest floor and the top of the canopy, which ul

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Dorbu, Freda, and Leila Hashemi-Beni. "Detection of Individual Corn Crop and Canopy Delineation from Unmanned Aerial Vehicle Imagery." Remote Sensing 16, no. 14 (2024): 2679. http://dx.doi.org/10.3390/rs16142679.

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Precise monitoring of individual crop growth and health status is crucial for precision agriculture practices. However, traditional inspection methods are time-consuming, labor-intensive, prone to human error, and may not provide the comprehensive coverage required for the detailed analysis of crop variability across an entire field. This research addresses the need for efficient and high-resolution crop monitoring by leveraging Unmanned Aerial Vehicle (UAV) imagery and advanced computational techniques. The primary goal was to develop a methodology for the precise identification, extraction,

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Zhang, Xuewei, Kefei Zhang, Suqin Wu, et al. "An Investigation of Winter Wheat Leaf Area Index Fitting Model Using Spectral and Canopy Height Model Data from Unmanned Aerial Vehicle Imagery." Remote Sensing 14, no. 20 (2022): 5087. http://dx.doi.org/10.3390/rs14205087.

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The leaf area index (LAI) is critical for the respiration, transpiration, and photosynthesis of crops. Color indices (CIs) and vegetation indices (VIs) extracted from unmanned aerial vehicle (UAV) imagery have been widely applied to the monitoring of the crop LAI. However, when the coverage of the crop canopy is large and only spectral data are used to monitor the LAI of the crop, the LAI tends to be underestimated. The canopy height model (CHM) data obtained from UAV-based point clouds can represent the height and canopy structure of the plant. However, few studies have been conducted on the

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Miraglio, Thomas, Karine Adeline, Margarita Huesca, Susan Ustin, and Xavier Briottet. "Monitoring LAI, Chlorophylls, and Carotenoids Content of a Woodland Savanna Using Hyperspectral Imagery and 3D Radiative Transfer Modeling." Remote Sensing 12, no. 1 (2019): 28. http://dx.doi.org/10.3390/rs12010028.

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Leaf pigment contents, such as chlorophylls a and b content (C a b ) or carotenoid content (Car), and the leaf area index (LAI) are recognized indicators of plants’ and forests’ health status that can be estimated through hyperspectral imagery. Their measurement on a seasonal and yearly basis is critical to monitor plant response and adaptation to stress, such as droughts. While extensively done over dense canopies, estimation of these variables over tree-grass ecosystems with very low overstory LAI (mean site LAI < 1 m 2 /m 2 ), such as woodland savannas, is lacking. We investigated the us

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Qian, Tingting, Yangxin Liu, Shenglian Lu, et al. "Cucumber Leaf Segmentation Based on Bilayer Convolutional Network." Agronomy 14, no. 11 (2024): 2664. http://dx.doi.org/10.3390/agronomy14112664.

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When monitoring crop growth using top-down images of the plant canopies, leaves in agricultural fields appear very dense and significantly overlap each other. Moreover, the image can be affected by external conditions such as background environment and light intensity, impacting the effectiveness of image segmentation. To address the challenge of segmenting dense and overlapping plant leaves under natural lighting conditions, this study employed a Bilayer Convolutional Network (BCNet) method for accurate leaf segmentation across various lighting environments. The major contributions of this st

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