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1. Hyperspectral Imaging Of Sugar Beet Symptoms Caused By Soil-borne OrganismsThe soil-borne pathogen Rhizoctonia solani and the plant parasitic nematode Heterodera schachtii are the most important constraints in sugar beet production worldwide. Symptoms caused by fungal infection are yellowing of leaves and rotting of the beet tuber late in the cropping season. Nematode afflicted plants show stunted growth early in the cropping season and also leaf wilting late in the season when water stress often sets in. Due to the low mobility of soil-borne organisms, they are ideal... C. Hillnhuetter, A. Mahlein, R.A. Sikora, E. Oerke |
2. Contour Planting: A Strategy To Reduce Soil Erosion On Steep SlopesPractices that combine GPS-based guidance for terrain contouring and tillage for runoff detention have potential to increase water infiltration and reduce runoff. The objective of this study was to investigate contour planting as a means to reduce soil erosion on steep slopes of the Columbia Plateau dryland wheat region. An exploratory field study was conducted on a Ritzville... D.S. Long, S.B. Wuest, J.D. Williams, M.J. Bailey, |
3. Accounting For Spatial Correlation Using Radial Smoothers In Statistical Models Used For Developing Variable-rate Treatment PrescriptionsVariable-rate treatment prescriptions for use on commercial farms can be developed from embedded field trials on those farms. Such embedded trials typically involve non-random, high-density sampling schemes that result in large datasets and response variables exhibiting spatial correlation. In order to accurately evaluate the significance of the effects of the applied treatments and the measured field characteristics on the response of interest, this spatial correlation must be accounted for in... K.S. Mccarter, E. Burris |
4. Sensor And System Technology For Individual Plant Crop ScoutingSensor and system technologies are key components for automatic treatment of individual plants as well as for plant phenotyping in field trials. Based on experiences in research and application of sensors in agriculture the authors have developed phenotyping platforms for field applications including sensors, system and software development and application-specific mountings. Sensor and data fusion have a high potential by compensating varying selectivities... A. Ruckelshausen, K.V. Alheit, L. Busemeyer, R. Klose, A. Linz, K. Moeller, F. Rahe, M. Thiel, D. Trautz, U. Weiss |
5. Mapping the Leaf Area Index In Vineyard Using a Ground-Based LIDAR ScannerThe leaf area index (LAI) is defined as the one-sided leaf area per unit ground area and is probably the most widely used index to characterize grapevine vigour. However, direct LAI measurement requires the use of destructive leaves sampling methods which are costly and time-consuming and so are other indirect methods. Faced with these techniques, vineyard leaf area can be indirectly estimated using ground-based LIDAR sensors that scan the vines and get information about the geometry and/or structure... J. Arno, I. Del moral, A. Escolà , J. Company, J.A. MartÍnez-casasnovas, J. Masip, R. Sanz, J.R. Rosell |
6. The Effect of Leaf Orientation on Spray Retention on BlackgrassSpray application efficiency depends on the pesticide application method as well as target properties. A wide range of drop impact angles exists during the spray application process because of drop trajectory and the variability of the leaf orientation. As the effect of impact angle on retention is still poorly documented, laboratory studies were conducted... F. Lebeau, M. Massinon, P. Maréchal, H. Boukhalfa |
7. Toward More Precise Sugar Beet Management Based On Geostatistical Analysis Of Spatial Variabilty Within FieldsAbstract: Sugar beet (Beta vulgaris L.) yields in England are predicted to increase in the future, due to the advances in plant breeding and agronomic progress, but the intra-field variations in yield due to the variability in soil properties is considerable. This paper explores the within-field spatial variation in environmental variables and crop development during the growing season and their link to spatial variation in sugar beet yield.... A.J. Murdoch, S.A. Mahmood |
8. Pesticide Application Manager (PAM) - Decision Support In Crop Protection Based On Terrain-, Machine-, Business- And Public DataIntroduction Pesticide Application Manager (PAM) is a project, co-financed by the German Federal Office for Agriculture and Food (BLE) that aims to develop solutions for automating important processes in crop protection. Due to a series of rules and legal requirements for planning, implementation and documentation, crop protection is one of the most... B. Kleinhenz, M. Röhrig, M. Scheiber, J. Feldhaus, B. Hartmann, B. Golla, C. Federle , D. Martini |
9. Spatial Variability Of Soil Compaction In Annual Cycle Of Different Culture Of Cane Sugar Land Clay SandyThe assessment of soil compaction levels and choosing the best management system are very important in modern agriculture, aiming to prevent or at least restore their physical conditions to a satisfactory level. The renewal of sugar cane plantation happens on average every 5 or 6 years. The current way repeats a sequence compaction and decompaction events during successive cycles of sugarcane, which promotes breakdown of soil structure. During the harvesting and transportation, the... F.C. Masiero, B.B. Fernandes, S.P. Guerra, K.P. Lanças, I. Marasca |
10. The Most Sensitive Growth Stage To Quantify Nitrogen Stress In Sugarcane Using Active Crop Canopy SensorThe use of sensors that allow the application of nitrogen fertilizer at variable rate has been widely used by researchers in many agricultural crops, but without success in sugarcane, probably due to the difficulty of diagnosing the nutritional status of the crop for nitrogen (N). Active crop canopy sensors are based on the principle that the spectral reflectance curve of the leaves are modified by N level. Researchers in USA indicated that in-season N stress in corn can be detected... S.G. Castro, O.T. Kolln, H.S. Nakao, H.C. Franco, O. Braunbeck, P.S. Graziano magalhães, G.M. Sanches |
11. From Data to Decisions - Ag Technologies Provide New Opportunities and Challenges with On-Farm ResearchU.S. farmers are challenged to increase crop production while achieving greater resource use efficiency. The Nebraska On-Farm Research Network (NOFRN), enables farmers to answer critical production, profitability, and sustainability questions with their own fields and equipment. The NOFRN is sponsored by the University of Nebraska – Lincoln Extension and derives from two separate on-farm research efforts, the earliest originating in 1990. Over the course of the last 29 years,... L. Thompson, K. Glewen, N. Mueller, J. Luck |
12. Identifying and Filtering Out Outliers in Spatial DatasetsOutliers present in the dataset is harmful to the information quality contained in the map and may lead to wrong interpretations, even if the number of outliers to the total data collected is small. Thus, before any analysis, it is extremely important to remove these errors. This work proposes a sequential process model capable of identifying outlier data when compared their neighbors using statistical parameters. First, limits are determined based on the median range of the values of all the... L. Maldaner, J. Molin, T. Tavares, L. Mendez, L. Corrêdo, C. Duarte |
13. Delineation of Site-Specific Nutrient Management Zones to Optimize Rice Production Using Proximal Soil Sensing and Multispectral ImagingEvaluating nutrient uptake and site-specific nutrient management zones in rice in Costa Rica from plant tissue and soil sampling is expensive because of the time and labor involved. In this project, a range of measurement techniques were implemented at different vintage points (soil, plant and UAVs) in order to generate and compare nutrient management information. More precisely, delineation of site-specific nutrient management zones were determined using 1) georeferenced soil/tissue... J.E. Villalobos, J.S. Perret, K. Abdalla, C.L. Fuentes, J.C. Rodriguez, W. Novais |
14. Use of UAV Acquired Imagery As a Precision Agriculture Method for Measuring Crop Residue in Southwestern Ontario, CanadaResidue management on agriculture land is a practice of great importance in southwestern Ontario, where soil management practices have an important effect on Great Lakes water quality. The ability of tillage or planting system to maintain soil residue cover is currently measured by using one or more of the common methods, line transect (e.g. knotted rope, Meter stick) and photographic (grid, script, and image analysis) methods. Each of these techniques has various advantages and disadvantages;... A. Laamrani, A. Berg, M. March, A. Mclaren, R. Martin |
15. AgronomoBot: A Smart Answering Chatbot Applied to Agricultural Sensor NetworksMobile devices advanced adoption has fostered the creation of various messaging applications providing convenience and practicality in general communication. In this sense, new technologies arise bringing automatic, continuous and intelligent features for communication through messaging applications by using web robots, also called Chatbots. Those are computer programs that simulate a real conversation between humans to answer questions or do tasks, giving the impression that the person is talking... G.M. Mostaço, L.B. Campos, C.E. Cugnasca, I.R. Souza |
16. Comparison of the Performance of Two Vis-NIR Spectrometers in the Prediction of Various Soil PropertiesSpectroscopy has shown capabilities of predicting certain soil properties. Hence, it is a promising avenue to complement traditional wet chemistry analysis that is costly and time-consuming. This study focuses on the comparison of two Vis-NIR instruments of different resolution to assess the effect of the resolution on the ability of an instrument to predict various soil properties. In this study, 798 air dried and compressed soil samples representing different agro-climatic conditions across... M. Marmette, V. Adamchuk, J. Nault, S. Tabatabai, R. Cocciardi |
17. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital AgricultureAgriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira |
18. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast TrackAgriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues |
19. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart FarmCurrently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues |
20. Evaluation of Nitrogen Recommendation Tools for Winter Wheat in NebraskaAttaining both high yield and high nitrogen (N) use efficiency (NUE) simultaneously remains a current research challenge in crop production. Digital ag technologies for site-specific N management have been demonstrated to improve NUE. This is due to the ability of digital technologies to account for the spatial and temporal distribution of crop N demand and available soil N in the field which varies greatly according to... J. Cesario pereira pinto, L. Thompson, N. Mueller, T. Mieno, G. Balboa, L. Puntel |
21. Assessing the Distribution Uniformity of Broadcast-interseeded Cover Crops at Different Crop Stages by an Unmanned Aerial VehicleDrones can now carry larger payloads and have become more affordable, making them a viable option to use for broadcast-interseeding cover crops in the fall, prior to main crop harvest. This strategy has become popular in Ohio over the past two years. However, this new strategy arose quickly with a limited understanding of field performance of the drone’s distribution uniformity under different parameters such as rates, swath widths, speeds, or cash crop type. Therefore, the objective of... A.D. Thomas, J.P. Fulton, S. Khanal, O. Ortez, G. Mcglinch |
22. Site-specific Evaluation of Sensor-based Winter Wheat Nitrogen Tools Via On-farm ResearchCrop producers face the challenge of optimizing high yields and nitrogen use efficiency (NUE) in their agricultural practices. Enhancing NUE has been demonstrated by adopting digital agricultural technologies for site-specific nitrogen (N) management, such as remote-sensing based N recommendations for winter wheat. However, winter wheat fields are often uniformly fertilized, disregarding the inherent variability within the fields. Thus, an on-farm evaluation of sensor-based N tools is needed to... J. Cesario pinto, L. Thompson, N. Mueller, T. Mieno, L. Puntel, P. Paccioretti, G. Balboa |
23. Bio-Effectors As a Promising Tool for Precision Agriculture and Integrated Plant NutritionBio-effectors, such as microorganisms and active natural compounds, are of increasing interest as promising alternatives or substitutes to precarious agrochemicals. European and global markets (valued at 14.6 billion US$ in 2023) for agricultural biologicals (bio-pesticides, bio-fertilizers, and bio-stimulants) are predicted to grow at rates of more than 13.5 % per year. Improved availability and use efficiency of mineral nutrients, tolerance to abiotic stresses, yield and quality traits, as well... M. Weinmann, M. Nkebiwe, N. Weber, K. Bradacova, N. Morad-talab, U. Ludewig, T. Müller, G. Neumann, M. Raupp, K. Bradacova |
24. Transforming Precision Agriculture Education, Research and Outreach in Sub-saharan Africa Through Intra-africa CooperationProductivity and profitability of sub-Saharan (SSA) agriculture can be enhanced greatly through the adoption of precision agriculture technologies and tools. However, until 2020 when the African Plant Nutrition Institute (APNI) established the African Association for Precision Agriculture (AAPA), most SSA PA enthusiast worked in isolation. The AAPA was formed to innovate Africa’s agricultural industry by connecting PA science to its practice and disseminate PA tailored to the needs... K.A. Frimpong, S. Phillips, V. Aduramigba-modupe, N. Fassinou hotegni, M. Mechri, M. Mishamo, J.M. Sogbedji, Z. hazzoumi, R. Chikowo, M. Fodjo kamdem |
25. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming ContextThe increasing expansion of irrigated almond orchards in regions of southeast Spain, facing water scarcity, underscores the need for a more effective and precise monitoring of the crop water status to optimize irrigation scheduling and improve crop water use efficiency. Remote and proximal sensing, combining visible, multispectral and thermal capabilities at different scales allows to estimate water needs, detect and quantify crop water stress, or identify different productivity zones within an... |