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1. Remote Sensing of Nitrogen and Water Status on Boston Lettuce Transplants in a Greenhouse EnvironmentRemote sensing is the stand-off collection through the use of a variety of devices for gathering information on a given object or area. Applied as a warning tool in plant stock production, it is expected to help in the achievement of better, more uniform and more productive organic cropping systems. Remote sensing of vegetation targets can be achieved from the... N. Tremblay, P. Vigneault, M.Y. Bouroubi, M. Dorais, G.P. Gianquinto, M. Tempesta |
2. Active Optical Sensor Algorithms For Corn Yield Prediction And In-Season N Application In North DakotaA recent series of seventy seven field N rate experiments with corn (Zea mays, L.) in North Dakota was conducted. Multiple regression analysis of the characteristics of the data set indicated that segregating the data into those with high clay soils and those with medium textures increased the relationship between N rate and corn yield. However, the nearly linear positive slope relationship in high clay soils and coarser texture soils with lower yield productivity indicated... L. Sharma, H. Bu, R. Ashley, G. Endres, J. Teboh, D.W. Franzen |
3. Application Of Hyperspectral Imaging For Rapid And Non-Invasive Quantification Of Quality Of Mulberry FruitThis study investigated the potential of using hyperspectral imaging working in visible and short-wave near infrared region (380-1030 nm) for rapid and non-invasive determination of the total flavonoid in mulberry fruit. Mulberry fruit with its sweet flavor is widely used in jam, pies, tarts, wines, and liquor, and is a delicacy among humans and birds alike. The quality evaluation of mulberry is usually determined by chemical or sensory analysis. However these methods are not capable... L. Huang, H. Jin, Y. He, F. Liu, Y. Zhou |
4. 3D Map in the Depth Direction of Field for Precision AgricultureBy a change in eating habits with economic development and the global population growth, we have been faced with the need for increased food production again. In order to solve the food problem in the future, the introduction of agriculture organization is progressing in emerging countries as well as developed countries. However, the occurrence of natural disasters and abnormal weather, which is becoming a worldwide problem at present, is further weakening the crops of farm... H. Umeda, S. Shibusawa, Q. Li, K. Usui, M. Kodaira |
5. Using A Potable Spectroradiometer For In-Situ Measurement Of Soil Properties In A Slope Citrus FieldIn precision agriculture, rapid, non-destructive, cost-effective and convenient soil analysis techniques are needed for crop and soil management. However, the spatial variability of soil properties is consider to be high cost and time consuming to characterize using traditional soil analysis method. To achieve cost and time reduction, the potential benefits of in-situ measurement of soil spectra have been recognized. ... S. Shibusawa, H. Umeda, K. Usui, M. Kodaira, Q. Li |
6. Assessing Impact Of Precision On Agricultural Energy Requirements: Weed Control Case StudyThe anticipated world population increase demands growth in sustainable food production. The current trend is to use more efficient agricultural processes in order to increase food production. Precision agriculture (PA) technology provides the means to increase equipment productivity and field and input efficiency. The concept of small modular and scalable intelligent machines tries to address the challenge of more productivity with the goal of reduced cost and power. In addition,... S. Brian, O.M. Toledo, L. Tang |
7. A Comparison Of Performance Between UAV And Satellite Imagery For N Status Assessment In CornA number of platforms are available for the sensing of crop conditions. They vary from proximal (tractor-mounted) to satellites orbiting the Earth. A lot of interest has recently emerged from the access to unmanned aerial vehicles (UAVs) or drones that are able to carry sensors payloads providing data at very high spatial resolution. This study aims at comparing the performance of a UAV and satellite imagery acquired over a corn nitrogen response trial set-up. The nitrogen (N) response... P. Vigneault, N. Tremblay, M.Y. Bouroubi, C. Bélec, E. Fallon |
8. Melon Classification and Segementation Using Low Cost Remote Sensing Data DronesObject recognition represents currently one of the most developing and challenging areas of the Computer Vision. This work presents a systematic study of various relevant parameters and approaches allowing semi-automatic or automatic object detection, applied onto a study case of melons on the field to be counted. In addition it is of a cardinal interest to obtain the quantitative information about performance of the algorithm in terms of metrics the suitability whereof is determined by the final... T. Zhao, Y. Chen, J. Franzen, J. Gonzalez, Q. Yang |
9. Almond Canopy Detection and Segmentation Using Remote Sensing Data DronesThe development of Unmanned Aerial System (UAV) makes it possible to take high resolution images of trees easily. These images could help better manage the orchard. However, more research is necessary to extract useful information from these images. For example, irrigation schedule and yield prediction both rely on accurate measurement of canopy size. In this paper, a workflow is proposed to count trees and measure the canopy size of each individual tree. The performances of three different methods... T. Zhao, M. Cisneros, Y. Chen, Q. Yang, Y. Zhang |
10. Comparative Benefits of Drone Imagery for Nitrogen Status Determination in CornRemotely sensed vegetation data provide an effective means of measuring the spatial variability of nitrogen and therefore of managing applications by taking intrafield variations into account. Satellites, drones and sensors mounted on agricultural machinery are all technologies that can be used for this purpose. Although a drone (or unmanned aerial vehicle [UAV]) can produce very high-resolution images, the comparative advantages of this type of imagery have not been demonstrated. The goal of... N. Tremblay, K. Khun, P. Vigneault, M.Y. Bouroubi, F. Cavayas, C. Codjia |
11. Utilizing GPS Technology and Science to Improve Digital Literacy Among Students in Australia and the United States of AmericaA key issue facing regional, rural and remote communities, in both Australia and the United States of America (USA), is the low level of digital literacy among some cohorts of students. This is particularly the case for students involved in agricultural studies where it is commonly perceived that digital literacy is not relevant to their future occupation. However, this perception is far from the truth, as the reality of farming today means students who intend on entering the agricultural workforce... C.W. Knight, A. Cosby, M. Trotter |
12. Invasive and Non-Invasive Technology for Measuring Water Content of Crop Leaves in Greenhouse HorticultureMoisture status in the crop is closely related to various physiological activities of the crop. If we can measure the moisture status in the crop in real time, we can understand the photosynthetic activity, which is an important physiological activity for growing crops, and the movement of the product from photosynthesis. Therefore, we verified it is possible to measure water content of crop leaves nondestructively using invasive method and non-invasive method. As a non-invasive measurement method,... H. Umeda, K. Muramatsu, Y. Kawagoe, T. Sugihara, S. Shibusawa, Y. Iwasaki |
13. Pest Detection on UAV Imagery Using a Deep Convolutional Neural NetworkPresently, precision agriculture uses remote sensing for the mapping of crop biophysical parameters with vegetation indices in order to detect problematic areas, and then send a human specialist for a targeted field investigation. The same principle is applied for the use of UAVs in precision agriculture, but with finer spatial resolutions. Vegetation mapping with UAVs requires the mosaicking of several images, which results in significant geometric and radiometric problems. Furthermore, even... Y. Bouroubi, P. Bugnet, T. Nguyen-xuan, C. Bélec, L. Longchamps, P. Vigneault, C. Gosselin |
14. Estimating Corn Biomass from RGB Images Acquired with an Unmanned Aerial VehicleAbove-ground biomass, along with chlorophyll content and leaf area index (LAI), is a key biophysical parameter for crop monitoring. Being able to estimate biomass variations within a field is critical to the deployment of precision farming approaches such as variable nitrogen applications. With unprecedented flexibility, Unmanned Aerial Vehicles (UAVs) allow image acquisition at very high spatial resolution and short revisit time. Accordingly, there has been an increasing interest in... K. Khun, P. Vigneault, E. Fallon, N. Tremblay, C. Codjia, F. Cavayas |
15. Computer Vision Techniques Applied to Natural Scenes Recognition and Autonomous Locomotion of Agricultural Mobile RobotsThe use of computer systems in Precision Agriculture (PA) promotes the processes’ automation and its applied tasks, specifically the inspection and analysis of agricultural crops, and guided/autonomous locomotion of mobile robots. In this context, this research aims the application of computer vision techniques for agricultural mobile robot locomotion, settled through an architecture for the acquisition, image processing and analysis, in order to segment, classify and recognize patterns... L.C. Lugli, M.L. Tronco, A.J. Porto |
16. Use of Watering Hole Data As a Decision Support Tool for the Management of a Grazing Herd of CattleEstablish grazing practices would improve the welfare of the animals, allowing them to express more natural behaviours. However, free-range reduces the ability to monitor the animals, thus increase the time needed to intervene in the event of a health problem. To ease the adoption of grazing, farmer would benefit from autonomously collected indicators at pasture that identify abnormal behaviours possibly related to a health problem in a bovine. These indicators must be individualised and collected... J. Plum, B. Quoitin, I. Dufrasne, S. Mahmoudi, F. Lebeau |
17. Estimating Soil Carbon Stocks with In-field Visible and Near-infrared SpectroscopyAgricultural lands can be a sink for carbon and play an important role in offsetting carbon emissions. Current methods of measuring carbon sequestration—through repeated temporal soil samples—are costly and laborious. A promising alternative is using visible, near-infrared (VNIR) diffuse reflectance spectroscopy. However, VNIR data are complex, which requires several data processing steps and often yields inconsistent results, especially when using in situ VNIR measurements. Using... C.J. Ransom, C. Vong, K.S. Veum, K.A. Sudduth, N.R. Kitchen, J. Zhou |
18. Predicting Corn Emergence Uniformity with On-the-go Furrow Sensing TechnologyIntegration of proximal soil sensors into commercial row-crop planter components have allowed for a dense quantification of within-field soil spatial variability. These technologies have potential to guide real-time management decisions, such as on-the-go variable seeding rate or depth. However, little is known about the performance of these systems. Therefore, research was conducted in central Missouri, USA to determine the relationship between planter sensor metrics, and corn (Zea mays L.) ... L.S. Conway, C. Vong, N.R. Kitchen, K.A. Sudduth, S.H. Anderson |
19. Potential of UAS Multispectral Imagery for Predicting Yield Determining Physiological Parameters of CottonThe use of unmanned aerial systems (UAS) in precision agriculture has increased rapidly due to the availability of reliable, low-cost, and high-resolution sensors as well as advanced image processing software. Lint yield in cotton is the product of three physiological parameters: photosynthetically active radiation intercepted by canopy (IPAR), the efficiency of converting intercepted active radiation to biomass (RUE), and the ratio of economic yield to total dry matter (HI). The relationships... A. Pokhrel, S. Virk, J.L. Snider, G. Vellidis, V. Parkash |
20. Overcoming Educational Barriers for Precision Agriculture Adoption: a University Diploma in Precision Agriculture in ArgentinaThe lack of educational programs in Precision Agriculture (PA) has been reported as one of the barriers for adoption. Our goal was to improve professional competence in PA through education in crop variability, management, and effective practices of PA in real cases. In the last 20 years different efforts has been made in Argentina to increase adoption of PA. The Universidad Nacional de Rio Cuarto (UNRC) launched in 2021 the first University Diploma in PA, a 9-month program to train agronomist... G. Balboa, A. Degioanni, R. Bongiovanni, R. Melchiori, C. Cerliani, F. Scaramuzza, M. Bongiovanni, J. Gonzalez, M. Balzarini, H. Videla, S. Amin, G. Esposito |
21. The Evaluation of NDVI Response Index Consistency Using Proximal Sensors, UAV and SatellitesThe Response Index NDVI (RINDVI) is described as the response of crops to additional nitrogen (N) fertilizer. It is calculated by dividing the NDVI of the high-N plot (N-rich strip) by the NDVI of the zero-N plot or farmer's practice where less pre-plant N was applied (Arnall and al., 2016). RI values are used to predict yield and monitor top dress N fertilization. Many research has been carried out to determine the difference... S. Phillips, B. Arnall, M. Maatougui |
22. Simultaneously Estimating Crop Biomass and Nutrient Parameters Using UAS Remote Sensing and Multitask LearningRapid and accurate estimation of crop growth status and nutrient levels such as aboveground biomass, nitrogen, phosphorus, and potassium concentrations and uptake is critical with respect to precision agriculture and field-based crop monitoring. Recent developments in Uncrewed Aircraft Systems (UAS) and sensor technologies have enabled the collection of high spatial, spectral, and temporal remote sensing data over large areas at a lower cost. Coupled deep learning-based modeling approaches with... P. Kovacs, M. Maimaitijiang, B. Millett, L. Dorissant, I. Acharya, U.U. Janjua, K. Dilmurat |
23. Computer Vision by UAVs for Estimate Soybean Population Across Different Physiological Growth Stages and Sowing SpeedsSoybean (Glycine max (Linnaeus) Merrill) production in the United States plays a crucial role in agriculture, occupying a considerable amount of cultivated land. However, the costs associated with soybean production have shown a notable increase in recent years, with seed-related expenses accounting for a significant proportion of the total. This increase in costs is attributed to a number of factors, including the introduction of patented and protected genetic traits, as well as inflationary... F. Pereira de souza, L. Shiratsuchi, H. Tao, M. Acconcia dias, M. Barbosa, T. Deri setiyono, S. campos |
24. Optimizing Soybean Management with UAV RGB and Multispectral Imagery: a Neural Network Method and Image ProcessingPrecision agriculture (PA) has emerged as a fundamental approach in contemporary agricultural management, aimed at maximizing efficiency in the use of resources and improving crop productivity. The transition to so-called "agriculture 4.0" represents a revolution in the way technology is applied in the field, with an emphasis on digital and automated solutions such as UAVs (Unmanned Aerial Vehicles). These devices offer new capabilities for capturing high-resolution images, enabling... F. Pereira de souza, L. Shiratsuchi, H. Tao, M. Acconcia dias, M. Barbosa, T. deri setiyono, S. Campos |
25. Optimizing Chloride (Cl) Application for Enhanced Agricultural YieldThe optimization of chloride (Cl-) application rates is crucial for enhancing crop yields and reducing environmental impact in agricultural systems. This study investigates the relationship between chloride application rates and wheat yields, focusing on Club wheat cultivation in a 19.76-hectare field in Washington State. The target yield was set at 3765 kilograms per hectare, with seeding conducted at 67.24 kilograms per hectare using conservation tillage practices. Potassium chloride... F. Pereira de souza, R.P. Negrini, H. Tao |