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16 results for “crop monitoring”
Data and results for manuscript "Multi-frequency electrical impedance tomography as a non-invasive tool to characterize and monitor crop root systems "
<p>Root systems are essential in nutrient uptake and translocation, but are difficult to characterize non-invasively with existing methods. We propose electrical impedance tomography (EIT) as a new tool for the imaging and monitoring of crop root systems. In a laboratory experiment we demonstrate the capability of the method to capture physiological responses of root systems with high spatial and temporal resolution. We conclude that EIT is a promising functional imaging technique for crop roots.</p> <p>This package contains measured raw EIT data, electrical imaging results, spectral results from the Debye decomposition, and the Python scripts used to generate the plots in the manuscript.</p>
GEOGLAM Crop Monitor Sub-National Crop Calendars
<p>The GEOGLAM Crop Monitor Sub-National Crop Calendars are based on a combination of the best available data from different international agencies, national ministries, and expert knowledge of the country partners from GEOGLAM Crop Monitors. The crops covered are wheat, maize, rice, soybeans, sorghum, millet, beans, and teff. In locations where there are multiple cropping seasons, the seasons are numbered with the first being the largest producing season followed by the next largest, and so on. The crop calendars consist of five different phenological stages which are broadly applicable across most crops; Planting through Early Vegetative, Vegetative through Reproductive, Ripening through Harvest, End of Harvest, and Out of Season. The sub-national regions were built using the administrative level 1 FAO GAUL units as the basic building blocks since crop production statistics are typically readily available for most countries at this level and the crop calendars were designed to link crop conditions to potential yield and production within the GEOGLAM Crop Monitors. Agroecological zones, subnational statistics, and national partner inputs were then used to inform the formation process. This was done so that areas with similar phenological development timelines were grouped, >90% of national production was captured in the calendars, and the national production was relatively distributed among the sub-national regions, accounting for the multiple crops monitored per country. To provide a finer temporal detailed product, the crop calendars are displayed in bi-monthly steps.</p>
Figure 7. The outcomes of the Monitoring and Control of the Greenhouse soil and climate Conditions for tomato crops-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>In the past generation greenhouses it was enough to have one cabled measurement point in<br> the middle to provide the information to the greenhouse automation system. The system itself was<br> usually simple without opportunities to control locally heating, lights, ventilation or some other<br> activity, which was affecting the greenhouse interior climate. The optimal greenhouse climate and<br> soil adjustment can enable us to improve productivity and to achieve remarkable energy savings. In<br> this paper we proposed a multi-agent methodology for integrated management systems in<br> greenhouses. In this regards wireless sensor networks play a vital role to monitor greenhouse and<br> environment parameters. Each controlled process of the greenhouse environment is modeled as an<br> autonomous agent with its own inputs, its own outputs and its own interactions with the other<br> agents. Each agent acts autonomously, as it knows a priori the desired environmental set-points. In<br> this way, any possible conflicting decisions of conventional environmental control methodologies<br> are resolved through negotiations between the agents so that the possible optimal integrated solution<br> is achieved. The developed system is simple, cost effective, and easily installable.</p>
Precision Agriculture Yield Monitoring in Row Crop Agriculture at the Kellogg Biological Station, Hickory Corners, MI (1996 to 2013)
Dataset Abstract The LTER annual crops (corn, soy and wheat), treatments 1-4, are harvested annually using a combine equipped with a GPS and precision agriculture software to allow detailed yield measurements with coincident GPS latitude and longitude data.. original data source http://lter.kbs.msu.edu/datasets/40
Final eddy covariance dataset to support lessons from long-term monitoring of carbon gains and losses in cropping systems
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Moving eDNA surveys into crop protection: a case study on the application of cowpea associated pests monitoring
<p><strong>Custom reference database of the study "Moving eDNA surveys into crop protection: a case study on the application of cowpea associated pests monitoring".</strong></p>
Seasonal monitoring of Drosophila suzukii and its non-crop hosts in Wuhu, Eastern China
<p><i>Drosophila</i><i> suzukii</i> (Matsumura) (Diptera: Drosophilidae) is a serious pest that prefers fresh fruits native to Southeast Asia. In our study apple cider vinegar bait traps were used to capture and monitor the population dynamics of this native pest in Wuhu City, China, from May/June, 2017 to May, 2018. The research was conducted at 15 locations in two fruit orchards in Wuhu. Traps caught more adults in general in Meiling blueberry orchard than in Xicun mixed orchard, and the highest trap counts occurred near harvest time (October). Females had more mature eggs from September to November and the number of mature eggs declined thereafter. We found several non-crop hosts of this pest, which can provide food and reproductive resources for <i>D. suzukii</i>, are common in forests and field margins. By comparing the number of captured adults in the Meiling and Xicun orchards, we found that blueberry was preferred by <i>D. suzukii </i>among the fruits in our search. Fruit ripening time differed among crops and therefore fly populations moved between crop and non-crop habitats during the year or had varying population dynamics on different crops in different seasons. The <i>D. suzukii</i> population and the number of mature eggs decreased in summer and winter but increased in spring and autumn. <i>Drosophila suzukii</i> had higher survival rates on blueberry than other fruits and <i>D. suzukii </i>could use four non-crop species growing around the orchards as host plants.</p>
CROSMOD project "Crop Stress Monitoring in the semi-arid context of Doukkala, Morocco" supported by ESA and AUC in the framework of EO AFRICA R&D Facility
<p>The CROSMOD project “Crop Stress Monitoring in the semi-arid context of Doukkala, Morocco” supported by ESA and AUC in the framework of EO AFRICA R&D Facility, aimed at developing a procedure for crop yield estimates and extreme events crops shocks monitoring or pest and diseases by integrating multiple satellite data and water-energy-crop modelling, able to support farmers precision agriculture for the case of the Doukkala Irrigation area in Morocco. <strong>The project was run by: Chiara Corbari and Nicola Paciolla from Politecnico di Milano (Italy); and Fatima-ezzahra Elghandour and Youssef Houali from Chouaib Doukkali University (Morocco).</strong></p> <p>The dataset report the results from the three case studies, which are cultivated fields with alfalfa, sugar beet and wheat in Morocco (LE, H, net radiation, land surface temperature, ET, potential irrigation, LAI, soil moisture) generated from FEST-EWB-SAFY model.</p> <p>The crop-energy-water balance FEST-EWB-SAFY model (Corbari et al., 2022) couples the distributed energy-water balance FEST-EWB (Corbari et al, 2011), which allows computing continuously in time and distributed in space both soil moisture and evapotranspiration fluxes, and the SAFY (Duchemin et al, 2008), simple model for yield prediction and plant development. FEST-EWB is based on the system of energy-water balances equations which are written in terms of a LST that allows closing the energy balance equation, so that this model internal variable can be directly compared with EO LST for model parameters calibration (Corbari & Mancini, 2014). The crop growth simple model (SAFY) (Duchemin et al, 2008) simulate yield and LAI prediction based on light-use efficiency theory with leaf partitioning function.</p> <p><strong>The code was developed by Chiara Corbari and Nicola Paciolla from Politecnico di Milano (Italy).</strong></p> <p>[1] Corbari, C., Ravazzani, G. and Mancini, M. (2011), A distributed thermodynamic model for energy and mass balance computation: FEST–EWB. Hydrol. Process., 25: 1443-1452. <a href="https://doi.org/10.1002/hyp.7910">https://doi.org/10.1002/hyp.7910</a></p> <p>[2] Corbari, C., Ben Charfi, I., Al Bitar, A., Skokovic, D., Sobrino, J.A., Perelli, C., Branca, G., Mancini, M. (2022), A fully coupled crop-water-energy balance model based on satellite data for maize and tomato crops yield estimates: The FEST-EWB-SAFY model, Agr. Wat. Man., 272: 107850. <a href="https://doi.org/10.1016/j.agwat.2022.107850%5Cn">https://doi.org/10.1016/j.agwat.2022.107850\n</a></p> <p>[3] Corbari, C., Mancini, M., 2014. Calibration and validation of a distributed energy water balance model using satellite data of land surface temperature and ground discharge measurements. J. Hydrometeorol. 15, 376–392. <a href="https://doi.org/10.1175/JHM-D-12-0173.1">https://doi.org/10.1175/JHM-D-12-0173.1</a></p> <p>[4] Duchemin, B., Maisongrande, P., Boulet, G., Benhadj, I., 2008. A simple algorithm for yield estimates: Evaluation for semi-arid irrigated winter wheat monitored with green leaf area index. Environ. Modell. Softw. 23(7), 876-892. <a href="https://doi.org/10.1016/j.envsoft.2007.10.003">https://doi.org/10.1016/j.envsoft.2007.10.003</a></p>
Seasonal monitoring of Drosophila suzukii and its non-crop hosts in Wuhu, Eastern China
Open the record for dataset details and reuse information.
Figure 4 from: Petrović-Obradović O (2013) Monitoring of aphid flight activities in seed potato crops in Serbia. ZooKeys 319: 333-346. https://doi.org/10.3897/zookeys.319.4315
Figure 4 - Dendrogram shows similarity between the sites, constructed on the basis of Morisita–Horn similarity index.
Figure 1 from: Petrović-Obradović O (2013) Monitoring of aphid flight activities in seed potato crops in Serbia. ZooKeys 319: 333-346. https://doi.org/10.3897/zookeys.319.4315
Figure 1 - Map of Serbia with monitored aphid flight activities sites. Coordinates of localities: Begeč 2007 (45°13'26"N, 19°36'53"E), Begeč 2008 (45°13'34"N, 19°37'23"E), Glumač 2008 (43°52'27"N, 20°1'1"E), Golija 1 2007 (43°27'45"N, 20°20'58"E), Golija 2 2007 (43°21'58"N, 20°32'12"E), Golija 1 2008 (43°26'25"N, 20°14'56"E), Golija 2 2008 (43°23'36"N, 20°24'53"E), Golija 1 2009 (43°24'6"N, 20°29'38"E), Golija 2 2009 (43°23'48"N, 20°18'31"E), Kotraža 2007 (43°42'7"N, 20°13'49"E), Kotraža 2008 (43°42'17"N, 20°13'34"E), Kotraža 2010 (43°41'49"N, 20°13'9"E), Kupusina 2008 (45°44'24"N, 19°0'6"E), Kupusina 2009 (45°43'49"N, 18°59'58"E), Stanišić 2008 (45°56'48"N, 19°10'51"E), Stanišić 2009 (45°57'7"N, 19°9'10"E), Stanišić 2010 (45°57'46"N, 19°11'6"E), Prijevor (43°54'49"N, 20°16'2"E), Zablaće 2 2009 (43°50'51"N, 20°26'51"E), Zablaće 1 2010 (43°50'27"N, 20°27'25"E).
Figure 2 from: Petrović-Obradović O (2013) Monitoring of aphid flight activities in seed potato crops in Serbia. ZooKeys 319: 333-346. https://doi.org/10.3897/zookeys.319.4315
Figure 2 - Maximum of Shannon–Weaver index per locality (number in brackets - number of weeks of monitoring aphid flight activities, number without brackets - week with maximum value of Shannon–Weaver index).
LTM_AC_crop: dataset of Long term monitoring of crop yield in young arable alley cropping systems in Belgium
<p>Dataset including results from crop yield and crop quality measurements obtained on a set of six alley cropping fields in Belgium during the first decade after their establishment. Sampled crops include maize, wheat, barley and potato. Measurements started in 2015 and are at present still continued. A transect approach is used in wich crop production is monitored at fixed distances from the trees (2m, 5m and 12m). Ton dry matter is assessed as well as crop specific quality parameters (a.o. for winter cereals: protein content & thousend kernel weight, silage maize: protein content & digestability, potato: under water weight and diameter fractions). For a detailed description of methodologies used see also: Pardon et al. (2018) (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.agsy.2018.08.008" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.agsy.2018.08.008</span></span></a>).</p>
Figure 6 from: Petrović-Obradović O (2013) Monitoring of aphid flight activities in seed potato crops in Serbia. ZooKeys 319: 333-346. https://doi.org/10.3897/zookeys.319.4315
Figure 6 - Vector pressure index for PLRV and most important vector per locality.
Figure 5 from: Petrović-Obradović O (2013) Monitoring of aphid flight activities in seed potato crops in Serbia. ZooKeys 319: 333-346. https://doi.org/10.3897/zookeys.319.4315
Figure 5 - Vector pressure index for PVY and most important vector per locality.
Figure 3 from: Petrović-Obradović O (2013) Monitoring of aphid flight activities in seed potato crops in Serbia. ZooKeys 319: 333-346. https://doi.org/10.3897/zookeys.319.4315
Figure 3 - Total Shannon–Weaver index diversity per locality.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.