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1. A New Approach to Yield Map CreationOne of the barriers to using yield maps as a data layer in precision agriculture activities is that the maps being generated to day are not very accurate in representing what really happened in field. Numerous data errors in the way the data is collected, poor calibration habits on the part of opera... C. Romier, M. Hyrien, D. Lamker |
2. Maximizing Agriculture Equipment Capacity Using Precision Agriculture TechnologiesGuidance systems are one of the primary Precision Agriculture technologies adopted by US farmers. While most practitioners establish their initial AB lines for fields based on previous management patterns, a potential exists in conducting analyses to establish AB lines or traffic patterns which maximize field capacity. The objective of this study was t... A.M. Poncet, T.P. Mcdonald, G. Pate, B. Tisseyre, J.P. Fulton |
3. A Step Towards Precision Irrigation: Plant Water Status Detection With Infrared ThermographyThe increasing demand for water all over the world calls for precision agriculture which accounts globally about 70 percent of all water withdrawal. Therefore, there is a need to optimizing water use efficiency and making the best use of available water for irrigation. Plant water status detection for advanced irrigation scheduling is frequently done by predawn leaf water potential (ΨPD) or leaf stomata conductance (gL) measurements. However, these measurements are time and labour consumi... S. Zia |
4. Timely, Objective, And Accurate Crop Area Estimations And Mapping Using Remote Sensing And Statistical Methods For The Province Of Prince Edward Island, CanadaThe provincial government of Prince Edward Island, Canada, required timely, objective, and accurate annual crop area statistics and mapping for 2006 to 2008. Consequently, Statistics Canada conducted a survey incorporating medium- resolution satellite imagery (10 to 30 m) and statistical survey methods. The objective was to produce crop area estimates with a coefficient of variation (CV) as a measure of accuracy, and to produce maps showing the distribution and location of different crops and... F. Bedard, G. Reichert, R. Dobbins, M. Pantel, J. Smith |
5. Estimation Of Sugar Beet Yield Brfore Harvesting Using Meteorological Data And Spot Satellite DataIn Japan, sugar beet is only cultivated in Hokkaido, the northernmost island. The area of sugar beet cultivation in Tokachi District is 30,000ha, which is equal to about 45% of the total national production area. Because sugar beet is suited to cool weather conditions, it is an important rotation crop in Hokkaido. The production of beet sugar in Hokkaido is about 640,000 tons, which is 75... C. Hongo, K. Niwa |
6. Low Cost High-resolution Aerial Photogrammetric Techniques For Precision Agriculture In Latin American CountriesOne of the first steps in precision agriculture is to obtain aerial images of an area of interest to determine soil units and management zones. Aerial and remote sensing information, digital elevation models and other spatial data are often inexistent in planning offices in Latin American countries and, up to now, enhancement and modifications have not been integrated into smaller scaled planning operation such as farming. High resolution remote sensing images from scanning satellites like Qu... J.S. Perret, O.E. arriaza, M.E. D, J. Aguilar |
7. Near Real-time Meter-resolution Airborne Imagery For Precision Agriculture: AerocamPrecision agriculture often relies on high resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require meter-solution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collabor... X. Zhang, C.R. Streeter, H. Kim, D.R. Olsen |
8. Determination Of Crop Injury From Aerial Application Of Glyphosate Using Vegetation Indices And GeostatisticsInjury to crops caused by off-target drift of glyphosate can seriously reduce growth and yield, and is of great concern to farmers and aerial applicators. Determining an indirect method for assessing the levels and extent of crop injury could support management decisions. The objectives of this study were to evaluate multiple vegetation indices (VIs) as surrogate variables for glyphosate injury identification and to evaluate the combined use of Geostatistical methods and the VIs to asse... B. Ortiz, S.J. Thomson, Y. Huang, K. Reddy |
9. Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea CropThe software SARI® has been developed to implement precision agriculture strategies through remote sensing imagery. It is written in IDL® and works as an add-on of ENVI®. It has been designed to divide remotely sensed imagery into “micro-images”, each corresponding to a small area (“micro-plot”), and to determine the quantitative agronomic and/or environmental biotic (i.e. weeds, pathogens) and/or non-biotic (i.e. nutrient levels) indicator... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, M. Gomez-casero, J.M. Pe, M. Jurado-exp, F. Lopez-granados, I. Castillejo-gonz, A. Garc |
10. Multi, Super Or Hyper Spectral Data, The Right Way From Research Toward Application In AgricultureRemote sensing provides opportunities for diverse applications in agriculture. One consideration of maximizing the utility of these applications, is the need to choose the most efficient spectral resolution. Picking the optimal spectral resolutions (multi, super or hyper) for a specific application is also influenced by other factors (e.g., spatial and temporal resolutions) of the utilized device. This work focuses mainly ... D.J. Bonfil, I. Herrmann, A. Pimstein, A. Karnieli |
11. Weeds Detection By Ground-level Hyperspectral ImagingWeeds are a severe pest in agriculture, causing extensive yield loss. Weed control of grass and broadleaf weeds is commonly performed by applying selective herbicides homogeneously all over the field. As presented in several studies, applying the herbicide only where needed has economical as well as environmental benefits. Combining remote sensing tools and techniques with the concept of precision agriculture has the potential to auto... U. Shapira , I. Herrmann, A. Karnieli, D.J. Bonfil |
12. Assessment Of Field Crops Leaf Area Index By The Red-edge Inflection Point Derived From Venus BandsThe red-edge region of leaves spectrum (700-800 nm) corresponds to the spectral region that connects the chlorophyll absorption in the red and the amplified reflectance caused by the leaf structure in the near infrared (NIR) parts of the spectrum. At the canopy level, the inflection point of the red-edge slope is influenced by the plant’s condition that is related to several properties, including Leaf Area Index (LAI) and plant nutritional ... I. Herrmann, A. Pimstein, A. Karnieli, Y. Cohen, V. Alchanatis , D.J. Bonfil |
13. Site-specific Management For Biomass Feedstock Production: Development Of Remote Sensing Data Acquisition SystemsEfficient biomass feedstock production supply chain spans from site-specific management of crops on field to the gate of biorefinery. Remote sensing data acquisition systems have been introduced for site-specific management, which is a part of the engineering solutions for biomass feedstock production. A stand alone tower remote sensing platform was developed to monitor energy crops using multispectral imagery. The sensing system was capable of collecting RGB and CIR images during the crop gr... T. Ahamed, L. Tian, Y. Zhang, Y. Xiong, B. Zhao, Y. Jiang, K. Ting |
14. Inversion Of Vertical Distribution Of Chlorophyll Concentration By Canopy Reflectance Spectrum In Winter WheatThe objective of this study was to investigate the inversion of foliage chlorophyll concentration(Chl) vertical-layer distribution by bidirectional reflectance difference function (BRDF) data, so as to provide guidance on the application of fertilizer. The ratio of transformed chlorophyll absorption reflectance index (TCARI) to optimized soil adjusted vegetation index (OSAVI) was named as canopy chlorophyll inversion index (CCII) ... W. Huang, C. Zhao |
15. Remote Estimation Of Gross Primary Production In MaizeThere is a growing interest in the estimation of gross primary productivity (GPP) in crops due to its importance in regional and global studies of carbon balance. We have found that crop GPP was closely related to its total chlorophyll content, and thus chlorophyll can be used as a proxy of GPP in crops. In this study, we tested the performance of various vegetation indices for estimating GPP. The indices were derived from spectral data collected remotely but at close-range over a period of e... A.A. Gitelson |
16. Artificial Neural Network Techniques To Predict Orange Spotting Disease In Oil PalmLarge-Scale oil palm plantations require timely detection of disease symptoms to enable effective intervention. Orange spotting is an emerging disease that significantly reduces oil palm productivity. Remote sensing technology offers the means to detect crop biophysical properties, including crop stress, in a cost effective and non destructive manner. In this study, different portable sensors were used to measure spectral reflectance and chlorop... S. Liaghat, S.K. Balasundram |
17. Comparison Of Different Vegetation Indices And Their Suitability To Describe N-uptake In Winter Wheat For Precision FarmingTo avoid environment pollution and to minimize the costs of using mineral fertilizers an efficient fertilization system, tailored to the plant needs becomes more and more important. For that, the essential information can be determined by detecting certain crop parameters, like dry matter of the plant biomass above ground, N-content and N-uptake. By using fluorescence and reflectance measurements of the canopy and the mathematical analysis these parameters are appreciable. In three ... M. Strenner, F. Maidl |
18. Use Of Spectral Distance, Spectral Angle, And Plant Abundance Derived From Hyperspectral Imagery To Characterize Crop Growth VariationVegetation indices (VIs) derived from remote sensing imagery are commonly used to quantify crop growth and yield variations. As hyperspectral imagery is becoming more available, the number of possible VIs that can be calculated is overwhelmingly large. The objectives of this study were to examine spectral distance, spectral angle and plant abundance derived from all the bands in hyperspectral imagery and compare them with eight widely used two-band or three-band VIs based on selected waveleng... C. Yang |
19. Soybean Canopy Response To Charcoal Rot In Arkansas: Observations Using Crop Circletm (ACS-470).Charcoal Rot caused by Macrophomina phaseolina is a problem to soybean production, especially in hot and dry areas of southern US. As an approach to develop a fast assessment method of this soil-borne disease, soybean canopy reflectance was recorded with an active optical sensor, the Crop CircleTM ACS-470 in 2009 from a microplot field in Fayetteville, Arkansas. The microplot experiment was designed as a completely randomized factorial experiment with four cultivars, two ino... S.S. Kulkarni, M. Doubledee, S.G. Bajwa, J.C. Rupe |
20. The Use Of A Ground Based Remote Sensor For Winter Wheat Grain Yield Prediction In Northern PolandThe aim of the research was to investigate if algorithms developed for winter wheat, cv. Trend, yield predictions, based on ground measured GNDVI, differ significantly between 2 sequent years. The research was conducted in Pomerania, northern Poland (54° 31' N 17° 18' E) on sandy loam soils. The strip-trial design was used to compare the effect of 6 N treatments: 0, 50, 100, 150, 200 and 250 kg ha-1, applied as one dose at the b... S.M. Samborski, D. Gozdowski, S.E. Dobers |
21. Assessment Of Pod Ceal Dc™ Effect On Grain Yield In Beans Using Multi-spectral Satellite Imagery And Yield DataPod Ceal DC™ from BrettYoung creates an elastic membrane over pods in canola, beans etc., which results in controlling shatter before combining. To carry out this on-farm experiment, an irrigated field was divided in two parts according to the yielding potential and topographical characteristics to ensure equal conditions for both variants of the experiment. Grain beans were grown in the field using conventional technology. Pod Ceal DC™ was applied three weeks before harvesting on... A. Melnitchouck |
22. Active Sensor For Real-time Determination Of Soil Organic MatterSoil organic matter influences chemical and physical properties in the root zone as well as soil biological activity and plant vigor. As such, it is reasonable to assume that there are probably opportunities for producers to incorporate soil organic matter concentration information into their management decisions. However, soil organic matter is usually notoriously variable within fields. An active sensor based on in-soil reflectance was developed to provide apparent real-tim... J. Schepers, K.H. Holland |
23. Management Of Remote Imagery For Precision AgricultureSatellite and airborne remotely sensed images cover large areas, which normally include dozens of agricultural plots. Agricultural operations such as sowing, fertilization, and pesticide applications are designed for the whole plot area, i.e. 5 to 20 ha, or through precision agriculture. This takes into account the spatial variability of biotic and of abiotic factors and uses diverse technologies to apply inputs at variable rates, fitted to the needs of each small defined area, i.e. 25 to 200... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, J.M. Pe, M. Jurado-exp, I. Castillejo-gonz, A. Garc, F. Lopez-granados, L. Prassack |
24. Multisensor Data Fusion Of Remotely Sensed Imagery For Crop Field MappingA wide variety of remote sensing data from airborne hyperspectral and multispectral images is available for site-specific management in agricultural application and production. Aerial imaging system may offer less expensive and high spatial resolution imagery with Near Infra-Red, Red, Green and Blue spectral wavebands. Hyperspectral sensor provides hundreds of spectral bands. Multisensor data fusion provides an effective paradigm for remote sensing applications by sy... Y. Lan, H. Zhang, C. Yang, D. Martin, R. Lacey, Y. Huang, W.C. Hoffmann, P. Moulton |
25. Apparent Electrical Conductivity Calibration In Semiarid Soils: Ion-pair CorrectionThe electromagnetic induction sensor (EM38DD) is a field proven portable sensor for rapid measurement of the apparent electrical conductivity (ECa) of soils. Calibration with the electrical conductivity of saturation paste extracts is the most widely used method to correlate ECa with the effective electrical conductivity (ECe). A drawback of this method is the formation of ion pairs in the high ionic strength saturated paste extracts, which effectively decreases the measured ECe, leading to t... X. Amakor, A.R. Jacobson, G.E. Cardon, A. Hawks, W. Barnes |
26. Nitrogen And Water Stress Impacts Hard Red Spring Wheat (Triticum Aestivum) Canopy ReflectanceRemote sensing-based in-season N recommendations have been proposed as a technique to improve N fertilizer use efficiency. Remote sensing estimation of South Dakota hard red spring wheat N requirements needs assessment. Research objectives were: (1) determine the effect of an in-season N application on grain yield, yield loss to nitrogen stress (YLNS), and grain protein; and (2) assess if remote sensing collected at different growth stages may be used to predict yie... C.L. Reese, D.E. Clay, D.L. Beck, S.A. Clay, D.S. Long, M. Shahinian |
27. Using A Surface Energy Model (reset) To Determine The Spatial Variability Of ET Within And Between Agricultural FieldsRemote sensing algorithms are currently being used to estimate regional surface fluxes (e.g. evapotranspiration (ET)). Many of these surface energy balance models use information derived from satellite imagery such as aircraft, Landsat, AVHRR, ASTER, and MODIS to estimate ET. The remote sensing approach to estimating ET provides advantages over traditional methods. One of the most important advantages is that it can provide estimates of actual ET for each pixel in the image. Most conventional... L. Garcia, A. Elhaddad |
28. NDVI 'Depression' In Pastures Following GrazingPasture biomass estimation from normalized difference vegetation index (NDVI) using ground, air or space borne sensors is becoming more widely used in precision agriculture. Proximal active optical sensors (AOS) have the potential to eliminate the confounding effects of path radiance and target illumination conditions typically encountered using passive sensors. Any algorithm that infers the green fraction of pasture from NDVI must factor in plant morphology and live/dead plant ratio, irrespe... J.S. Stanley, D.W. Lamb, M.G. Trotter, M.M. Rahman |
29. Multitemporal Satellite Imaging To Support Near Real-Time Precision FarmingThis paper presents a 2014 update on the DMC constellation of optical satellite sensors and how they are exploited for various types of agricultural monitoring. Thousands of farmers around the world are exploiting this powerful data source for the management of crops, enabled by specialist service providers which convert the imagery into meaningful biophysical measurements and spatially variable nitrogen/irrigation recommendations. The paper also looks ahead to future ... G. Holmes |
30. Detection Of Fruit Tree Water Status In Orchards From Remote Sensing Thermal ImageryIn deciduous fruit trees there is a growing need of using water status indicators for scheduling irrigation and adopt regulated deficit irrigation (RDI) strategies taking into account spatial variability of orchards. RDI strategies have been successfully adopted for many fruit trees as a means for reducing water use and because yield and quality at harvest are not sensitive to water stress at some developmental stages. Although water status is generally monitored by measuring tr... P.J. Zarco-tejada, V. Gonzalez-dugo, J. Girona, E. Fereres, J. Bellvert |
31. An Evaluation Of HJ-CCD Broadband Vegtation Indices For Leaf Chlorophyll Content EstimationLeaf chlorophyll content is one of the most important biochemical variables for crop physiological status assessment, crop biomass estimation and crop yield prediction in precision agriculture. Vegetation indices were considered effective for chlorophyll content estimation. Although hyperspectral reflectance is proven to be better than multispectral reflectance for leaf chlorophyll content retrieval, the scarcity of available data from satellite hyperspectra... T. Dong, J. Shang, J. Meng, J. Liu |
32. Near-Real-Time Remote Sensing And Yield Monitoring Of Biomass CropsThe demand for bioenergy crops production has increased tremendously by the biofuel industry for substitution of traditional fuels due to the economic availability and environmental benefits. Pre-Harvest monitoring of biomass production is necessary to develop optimized instrumentation and data processing systems for crop growth, health and stress monitoring; and to develop algorithms for field operation scheduling. To cope with the problems of missing criti... Y. Zhao, L. Li, K.C. Ting, L.F. Tian, T. Ahamed |
33. Evaluating Soil Nutrition Status With Remote Sensing Derived Land ProductivityAvailable nitrogen is the amount of this nutrient available to plants in the soil and the amount of nitrogen provided by fertilizers. Compared to total nitrogen, nitrogen availability is a more useful tool for determining how much fertilizer you need and when to apply it. Determining the level of nitrogen available in field soil is also a useful method to increase the efficiency of fertilizer. Most soil properties are time-consuming and costly to measure, and also change over ti... Z. Chen, J. Meng, X. You |
34. Design, Development And Application Of A Satellite-Based Field Monitoring System To Support Precision FarmingThe factual base of precision agriculture (PA) - the spatial and temporal variability of soil and crop factors within or between different fields has been recognized for centuries. Field information on seeding suitability, soil & crop nutrition status and crop mature date is needed to optimize field management. How to acquire the spatially and temporally varied field parameters accurately, efficiently and at affordable cost has always been the focus of the researches in the ... Z. Li, B. Wu, J. Meng |
35. Creation Of Prescription For Optimal Nitrogen Fertilization Through Evaluation Of Soil Carbon Amount Using Remotely Sensed DataIn these years, drastic increase of agricultural production costs has been induced, which was triggered by the sharp rise of costs relating to agricultural production materials such as fertilizers and oil. In Japan, the substantial negative influence is anticipated to spread over to management of the farmers particularly in Hokkaido, the northern part of Japan. As one of the measures against this influence, a plan of effective fertilizer application and ... E. Tamura, K. Aijima, K. Niwa, O. Nagata, K. Wakabayashi, C. Hongo |
36. Study On Plant Health Condition Monitoring Using Acoustic Radiation ForceIn recent years, irrigation method using the negative pressure difference attracts attention from the point of view of water saving. In addition, it is proved that this technique is effective in upbringing of the plant as well as saving of water. By measuring water distribution of soil, active irrigation control will be performed In our previous study, we confirmed that the resonance frequency of a leaf is influenced by the water stress to the plant. Thus the vibration measureme... Y. Nakagawa, M. Sano, T. Shirakawa, K. Yamagishi, T. Sugihara, M. Ohaba, S. Shibusawa, T. Sugimoto |
37. Spectral High-Throughput Assessments Of Phenotypic Differences In Spike Development, Biomass And Nitrogen Partitioning During Grain Filling Of Wheat Under High Yielding Western European ConditionsSingle plant traits such as green biomass, spike dry weight, biomass and nitrogen (N) transfer to grains are important traits for final grain yield. However, methods to assess these traits are laborious and expensive. Spectral reflectance measurements allow researchers to assess cultivar differences of yield-related plant traits and translocation parameters that are affected by different genetic material and varying amounts of available N. In a field experiment, six high-yielding wheat c... U. Schmidhalter, K. Erdle |
38. Monitoring Ratio Of Leaf Carbon To Nitrogen In Winter Wheat Based On Hyperspectral MeasurementsThe metabolic status of carbon (C) and nitrogen (N) as two essential elements of crop plants has significant influence on the ultimate formation of yield and quality in crop production. Leaf is the major organ of plant photosynthesis and physiological activity, and in leaf tissues the ratio of carbon to nitrogen (C/N), defined as the ratio of LCC (leaf carbon concentration) to LNC (leaf nitrogen concentration), can... X. Xu |
39. An Inexpensive Aerial Platform For Precise Remote Sensing Of Almond And Walnut Canopy TemperatureCurrent irrigation practices depend largely on imprecise applications of water over fields with varying degrees of heterogeneity. In most cases, the amount of water applied over a given field is determined by the amount the most water-stressed part of the field needs. This equates to over-watering most of the field in order to satisfy the needs of one part of the field. This approach not only wastes resources, but can have a detrimental effect on the value of that crop. A system t... K. Crawford, S. Upadhyaya, R. Dhillon, F. Rojo, J. Roach |
40. Automatic Detection And Mapping Of Irrigation System Failures Using Remotely Sensed Canopy Temperature And Image ProcessingToday there is no systematic way to identify and locate failures of irrigation systems mainly because of the labor costs associated with locating the failures. The general aim of this study was to develop an airborne thermal imaging system for semi - automatic monitoring and mapping of irrigation system failures, specifically, of leaks and clogs. Initially, leaks and clogs were simulated by setting controlled trials in table grapes vineyards and olive groves. Airborne ther... V. Alchanatis, Y. Cohen, M. Sprinstin, A. Cohen, I. Zipori, A. Dag, A. Naor |
41. Are Thermal Images Adequate For Irrigation Management?Thermal crop sensing technologies have potential as tools for monitoring and mapping crop water status, improving water use efficiency and precisely managing irrigation. As thermal sensors and imagers became more affordable, various platforms were examined to allow for canopy- and field-scale acquisitions of canopy temperature and to extract maps of water status variability. Various canopy temperature statistics and crop water stress index (CWSI) were used to estimate water stat... O. Rosenberg, V. Alchanatis, Y. Saranga, A. Bosak, Y. Cohen |
42. Estimation of Vegetative Biomass Using On-the-Go Mobile SensorsNon-destructive methods for estimation of vegetative biomass have been developed using several remote sensing strategies as well as physical measurement techniques. An effective method for estimating biomass must be at least as accurate as the accepted standard for destructive removal measurement techniques such as a forage harvester or quad harvest strategies. In large part vegetative biomass is considered a function of canopy or plant height. Subsequently, a method o... J. Pittman |
43. Use Of Quality And Quantity Information Towards Evaluating The Importance Of Independent Variables In Yield PredictionYield predictions based on remotely sensed data are not always accurate. Adding meteorological and other data can help, but may also result in over-fitting. Working with American Crystal Sugar, we were able to demonstrate that the relevance of independent variables can be tested much more reliably when not only yield but also quality attributes are known, such as the sugar content and the s... E. Momsen, J. Xu, D.W. Franzen, J.F. Nowatzki, K. Farahmand, A.M. Denton |
44. A Case Study Approach for Teaching and Applying Precision AgricultureStudents often struggle understanding precision agriculture principles and how these principles can be applied to farming operations. A case-study approach that requires students to own a recreational global positioning system (GPS) for collecting on-farm data could be a method for helping students understand and apply precision agriculture. This paper describes a case-study approach to teaching precision agriculture using student owned GPS units and geographical information systems (GIS) sof... J.D. Williams |
45. Map@Syst – Geospatial Solutions for Rural and Community SustainabilityMap@Syst is a part of the USDA Cooperative State Research, Education and Extension Service (CSREES) eXtension online Web information service. eXtension is an educational partnership of more than 70 universities to provide online access to objective, research-based information and educational opportunities. Map@Syst is a Wiki-based Web site assembled and maintained cooperatively by geospatial technology educational specialists and practitioners. Map@Syst is a primary source of geospatial infor... P. Rasmussen, J. Nowatzki |
46. Teaching Critical Thinking Skills Using Geospatial Technology As Instructional ToolsTechniques in data collection and analysis of data are important concepts for students of precision farming. Also needed in conjunction with these concepts are critical thinking and problem solving skills. Employers often list critical thinking skills as one of the most important characteristics for new employees. Helping students experience and acquire critical thinking skills can be difficult. Geospatial technologies are not only useful precision farming tools, they are also educational too... T.A. Brase |
47. Increasing Profitability & Sustainability of Maize Using Site-Specific Crop Management in New ZealandPrecision agriculture (PA) tools and techniques have been used in New Zealand (NZ) since the early 1990's. There has been wide-scale uptake of some PA tools such as autosteer; planter and sprayer section control; and variable-rate irrigation. However, there has been a limited uptake of Site-Specific Crop Management (SSCM) using variable-rate seeding, nutrient and lime applications to different Management Zones (MZ). This paper outlines examples of the use of SSCM on maize crops,... A.W. Holmes, G. Jiang |
48. Potential of Apparent Soil Electrical Conductivity to Describe Soil Spatial Variability in Brazilian Sugarcane FieldsThe soil apparent electrical conductivity (ECa) has been highlighted in the literature as a tool with high potential to map the soil fertility of fields. However, sugarcane fields still lack results that show the applicability of this information to define the soil spatial variability and its fertility conditions. The objective of the present paper was to provide a comprehensive assessment of the relationship between ECa, evaluated by electromagnetic induction (EMI) sensor, and the spatial va... G.M. Sanches, P.S. Magalhães, H.C. Franco, A.Z. Remacre |
49. Spatial Variability of Canola Yield Related to Terrain Attributes Within Producer's FieldsCanola production in the Canadian Prairies varies considerably within and between producer's fields. This study describes the variability of crop yield in producer's fields in the context of terrain attributes, and in relation to fertilizer rates in management zones determined from historical yield. Canola yield data were collected for 27 fields in Alberta, Saskatchewan and Manitoba Canada in 2014, 2015, 2016 and 2017. Several terrain attributes accounted for a consi... A. Moulin, M. Khakbazan |
50. Soil Spatial Variability Assessment and Precision Nutrient Management in Maize (Zea Mays L.)Investigations on soil spatial variability and precision nutrient management based targeted yield approach in maize was carried out at Agricultural research station (ARS), Mudhol (Karnataka), India under irrigated condition during 2013-14, 2014-15 and 2015-16. ARS, Mudhol is located in northern dry zone of Karnataka at 160 20! N latitude, 750 15! E longitude and at an altitude of 577.6 meter above mean sea level. To assess the spatial variability, the study area was divided into 20 x20 m size... M.P. Potdar, G.B. Balol, S.A. Satyareddi, B.T. Nadagouda , C.P. Chandrashekar |
51. Variability in Corn Yield Response to Nitrogen Fertilizer in QuebecOptimizing nitrogen (N) fertilization is important to improve corn yield and to reduce N losses to the environment. The economic optimum nitrogen rate (EONR) is variable and depends on many factors, including weather conditions and crop management. The main objective of this study was to examine how grain corn yield response to N varies with planting date, soil texture and spring weather across sites and years in Monteregie, which is the most important with 64% of total area and 6... L. Kablan, V. Chabot, A. Mailloux, M. Bouchard, D. Fontaine, T. Bruulsema |
52. Frameworks for Variable Rate Application of ManureWorldwide, nitrogen (N) and phosphorus (P) losses from agriculture are main contributors to eutrophication of water bodies so that forceful agro-technical measures are required to reduce their diffuse discharge to the environment. With view to worldwide finite mineral rock phosphates efficient standards are required to close the agricultural P cycle. In intensive agricultural livestock production manure is often treated as a waste problem rather than an organic fertilizer and source of nutrie... H. Lilienthal, S.H. Haneklaus, E. Schnug |
53. The Profitability of Variable Rate Lime in WheatGrid sampling allows a variable rate of lime to be applied and has been marketed as a cost saver to producers. However, there is little research that shows if this precision application is profitable or not. Previous research on variable-rate lime has considered only a small number of fields. This paper uses soil sampling data from 170 fields provided by producers in Oklahoma and Kansas. We compare net returns of variable rate to uniform rate lime for grain only wheat production, dual-purpose... B. Mills, B. Brorsen, D. Arnall |
54. Flat Payoff Functions and Site-Specific Crop ManagementWithin the neighbourhood of any economically “optimal” management system, there is a set of alternative systems that are only slightly less attractive than the optimum. Often this set is large; in other words, the payoff function is flat within the vicinity of the optimum. This has major implications for the economics of variable-rate site-specific crop management. The flatter the payoff function, the lower the benefits of precision in the adjustment of input rates spatially withi... D. Pannell, A. Weersink, M. Gandorfer |
55. Increasing Corn (Zea Mays L.) Profitability by Site-Specific Seed and Nutrient Management in Igmand-Kisber Basin, HungaryVariable Rate Technology (VRT) in seeding and nutrient management has been developed in order to apply crop inputs variably. Farm equipment is widely available to manage in-field variability in Hungary, however, defining management zones, seed rates and amounts of nutrients is still a challenge. An increasing number of growers in Hungary have started adopting precision agriculture technology; however, data on profitability concerning site-specific seeding and nitrogen management is not widely... G. Milics, S. Szabó, K. Bűdi, A. Takács, V. Láng, S. Zsebo |
56. Modifying Agro-Economic Models to Predict Effects of Spatially Varying Nitrogen on Wheat Yields for a Farm in Western AustraliaAgricultural research in broadacre farming in Western Australia has a strong history, resulting in a significant public resource of knowledge about biophysical processes affecting crop performance. However, translation of this knowledge into improved on-farm decision making remains a challenge to the industry. Online and mobile decision support tools to assist tactical farm management decisions are not widely adopted, for reasons including: (1) they take too much time and training to learn; a... F.H. Evans, J. Andrew, C. Scanlan, S. Cook |
57. Field Level Management and Data Verification of Variable Rate Fertilizer ApplicationIncreased cost efficiencies and ease of use make spinner-disc spreaders the primary method of applying fertilizers throughout much of the United States. Recently, advances in spreader systems have enabled multiple fertilizer products to be applied at variable application rates. This provides greater flexibility during site-specific management of in-field fertility. Physical and aerodynamic properties vary for fertilizer granules of different sources and densities, these properties in turn aff... R. Colley iii, J. Fulton, S. Virk, E. Hawkins |
58. Integration of Proximal and Remote Sensing Data for Site-Specific Management of Wild BlueberryIn Saguenay-Lac-St-Jean, there are nearly 27,000 ha of wild blueberries (Vaccinium angustifolium Ait.). This production is carried out in fields with heterogeneous growing conditions due to the local changes in topography, key soil properties, and crop density. The main objective of this study was to develop a regression-based approach to site-specific management (SSM) by integrating proximally and remotely sensed data layers, namely, apparent soil electrical conductivity (ECa), field elevati... A. Johnston, V. Adamchuk, A. Biswas, A. Cambouris, J. Lafond, I. Perron |
59. Optimizing Corn Seeding Depth by Soil Texture to Achieve Uniform StandCorn (Zea mays L.) yield potential can be affected by uneven emergence. Corn emergence is influenced by both management and environmental conditions. Varying planting depth and rate as determined by soil characteristics could help improve emergence uniformity and grain yield. This study was conducted to assess varying corn seeding depths on plant emergence uniformity and yield on fine- and coarse-textured soils. Research was conducted on alluvial soil adjacent to the Missouri river with contr... S. Stewart, N. Kitcken, M. Yost, L. Conway |
60. Development of a Graphical User Interface for Spinner-Disc Spreader Calibration and Spread Uniformity AssessmentBroadcast fertilizer distribution through spinner-disc spreaders remain the most cost-effective, and least time consuming process to apply the needed soil amendments for the next crop. Spreaders currently available to producers enable them to apply a variety of granular products at varying rates, blends, and swath widths. In order to uniformly apply granular fertilizer or lime, the spreader should be calibrated by standard pan testing with any change in spreader settings, application rate, or... R. Colley iii, Y. Lin, J. Fulton, S. Shearer |
61. soil2data: Concept for a Mobile Field Laboratory for Nutrient AnalysisKnowledge of the small-scale nutrient status of arable land is an important basis for optimizing fertilizer use in crop production. A mobile field laboratory opens up the possibility of carrying out soil sampling and nutrient analysis directly on the field. In addition to the benefits of fast data availability and the avoidance of soil material transport to the laboratory, it provides a future foundation for advanced application options, e.g. a high sampling density, sampling of small sub-fie... V. Tsukor, C. Scholz, W. Nietfeld, T. Heinrich, T. Mosler , F. Lorenz, E. Najdenko, A. Möller, D. Mentrup, A. Ruckelshausen, S. Hinck |
62. Rapid Acquisition of Site Specific Lime Requirement with Mid-Infrared SpectroscopyIn Germany, the lime requirement of arable topsoils is derived from the organic matter content, clay content, and pH(CaCl2). For this purpose, it is common practice to determine the lime requirement of a field size up to three hectares from only one composite soil sample, whereby site heterogeneity is regularly not taken into account. To consider site heterogeneity, a measurement technique is required which allows a rapid and high resolution data acquisition. Mid-infrared... M. Leenen, S. Pätzold, T. Heggemann, G. Welp |
63. Design and Performance Experiment of an Outer Grooved-Wheel Fertilizer Apparatus with the Helical ToothTraditional outer groove-wheel fertilizer apparatus (OGWFA) with the straight tooth exists the problem of breakage and pulsation in the fertilizing process. A new type of OGWFA with the helical tooth has been designed to solve this problem, and the amount of fertilizer can be adjusted. The helix angle of the helical tooth has been optimized by theory analysis and DEM simulation. It reveals that the helix angle should be ranged from 34.4° to 68.8°. The performances of the OGWFA with th... D. Jun, X. Junfang, Z. Wangyuan, W. Qiaohua, D. Youchun, S. Caixia, Z. Zhihui |
64. Soil and Crop Factors to Site-specific Nitrogen Management on Sugarcane FieldsNitrogen (N) is one of the most widely used fertilizers in crops and the most harmful to the environment. The increase fertilizers consumption, mainly N sources (one of the most widely fertilizer used in sugarcane fields), is one of the main factors underlying the sustainability of the entire production process. Currently, N recommendations in sugarcane are based only on the expected yield. However, there is little agronomic support for nitrogen (N) recommendations based on expected yield, de... G.M. Sanches, R. Otto, F.R. Pereira |
65. Spatial and Temporal Factors Impacting Incremental Corn Nitrogen Fertilier Use EfficiencyCurrent tools for making crop N fertilizer recommendations are primarily based on plot and field studies that relate the recommendation to the economic optional N rate (EONR). Some tools rely entirely on localized EONR (e.g., MRTN). In recent years, tools have been developed or adapted to account for within-field variation in crop N need or variable within season factors. Separately, attention continues to elevate for how N fertilizer recommendations might account for environmenta... N.R. Kitchen, C.J. Ransom, J.S. Schepters, J.L. Hatfield, R. Massey |
66. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and IndianaPrecision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minne... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor |
67. Nitrogen Fertilization of Potato Using Management Zone in Prince Edward Island, CanadaPotato is sensible to nitrogen (N) and optimal N fertilization improve the tuber yield and its quality. Potato crop N response varies widely within fields. It is also well recognized that significant spatial and temporal variation in soil N availability occurs within crop fields. However, uniform application of N fertilizer is still the most common practice under potato production. Management zone (MZ) approach can help growers to achieve a part of this. The goal of the project is to compare ... A. Cambouris, M. Duchemin, N. Ziadi |
68. Evaluating the Potential of Improving In-season Nitrogen Status Diagnosis of Potato Using Leaf Fluorescence Sensors and Machine LearningPrecision nitrogen (N) management is particularly important for potato crops due to their high N fertilizer demand and high N leaching potential caused by their shallow root systems and preference for coarse-textured soils. Potato farmers have been using a standard lab analysis called petiole nitrate-N (PNN) test as a tool to diagnose potato N status and guide in-season N management. However, the PNN test suffers from many disadvantages including time constraints, labor, and cost of analysis.... S. Wakahara, Y. Miao, S. Gupta, C. Rosen, K. Mizuta, J. Zhang, D. Li |
69. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 ImageryPasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of th... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães |
70. Variable Rate Nitrogen Approach in a Potato-wheat-wheat Cropping SystemNitrogen application in agriculture is a vital process for optimal plant growth and yield outcomes. Different factors such as topography, soil properties, historical yield, and crop stress affect nitrogen (N) needs within a field. Applying variable N within a field could improve precision agriculture. Optimal N management is a system that involves applying a conservative variable base rate at or shortly after planting followed by in-season assessment and, if needed, variable rate application&... E.A. Flint, M. Yost, B.G. Hopkins |
71. 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 t... J. Cesario pereira pinto, L. Thompson, N. Mueller, T. Mieno, G. Balboa, L. Puntel |
72. Nitrogen Placement Considerations for Maize Production in the Eastern US CornbeltProper fertilizer placement is essential to optimize crop performance and amount of applied nitrogen (N) along with crop yield potential. There exists several practices currently used in both research within farming operations on how and when to apply N to maize (Zea mays L). Split applications of N in Ohio is popular with farmers and provides an economic benefit but more recently some farmers have been using mid- and late-season N fertilizer applications for their maize production.&... J.P. Fulton, E. Hawkins, S. Shearer, A. Klopfenstein, J. Hartschuh, S. Custer |
73. In-season Nitrogen Management of Maize Based on Nitrogen Status and Lodging Risk PredictionDevelopment of effective precision nitrogen (N) management strategies is crucially important for food security and sustainable development. Lodging is one of the major constraints to increasing maize yield that can be induced by strong winds, and is also influenced by management practices, like N rate. When making in-season N application decisions, lodging risk should be considered to avoid yield loss. Little has been reported on in-season N management strategies that also incorporate lodging... R. Dong, Y. Miao, X. Wang |
74. Assessment of Active Crop Canopy Sensor As a Tool for Optimal Nitrogen Management in Dryland Winter WheatOptimum nitrogen (N) fertilizer application is important for agronomic, economic, and environmental reasons. Among different N management tools, active crop canopy sensors are a recent and promising tool widely evaluated for use in corn but still under-evaluated for use in winter wheat. The objective of this study was to determine whether vegetation indices derived from in-season active crop canopy sensor data can be used to predict winter wheat grain yield and protein content and subsequentl... D. Ghimire |
75. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather DataNitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by c... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia |
76. Temperature Effect on Wild Blueberry Fruit Quality During Mechanical HarvestMechanical harvesters, utilizing a range of technologies, have been developed for timely operations and remain the most cost-effective means of picking the wild blueberry crop. Approximately 95% of wild blueberries in Atlantic Canada are immediately frozen and processed, while only a small percentage is sold in the fresh market. However, the producers can benefit by increasing the value of their harvested crop through fresh market sales. The objective of this study was to determine the optimu... T.J. Esau, A.A. Farooque, F. Abbas |
77. Variable Rate Fertilization in a High-yielding Vineyard of Cv. Trebbiano Romagnolo May Reduce Nitrogen Application and Vigour Variability Without Loss of Crop LoadThe site-specific management of vineyard cultural practices may reduce the spatial variability of vine vigor, contributing to achieve the desired yield and grape composition. In this framework, variable rate fertilization may effectively contribute to reduce the different availability of mineral nutrients between different areas of the vineyard, and so achieving the vine’s aforementioned performances. The present study was aimed to apply a variable rate fertilization in a high... G. Allegro, R. Martelli, G. Valentini, C. Pastore, R. Mazzoleni, F. Pezzi, I. Filippetti, A. Ali |
78. Digital Soil Sensing and Mapping for Crop SuitabilitySoil, central to any land-based production system, determines the success of any crops. While soil for a farm or field is fixed, the crops can be selected to best fit the soil’s capability and production. Traditionally crops are selected based on farm history, knowledge, and years of trial and error to tailor the right crop to the right soil. Inherent challenges associated with this make the whole process unsustainable. Due to the consistent nature of the information collected, soil sen... D. Saurette, A. Biswas, T.B. Gobezie |
79. Assessing the Potential of Sentinel-1 in Retrieving Mango Phenology and Investigating Its Relation to Weather in Southern GhanaThe rise in global production of horticultural tree crops over the past few decades is driving technology-based innovation and research to promote productivity and efficiency. Although mango production is on the rise, application of the remote sensing technology is generally limited and the available study on retrieving mango phenology stages specifically, was focused on the application of optical data. We therefore sought to answer the questions; (1) can key phenology stages of mango be retr... B.A. Torgbor, M.M. Rahman, A. Robson, J. Brinkhoff |
80. Realising the Potential of Agricultural Robotics and AI: The Ethical ChallengesRecent advances in AI and robotics may dramatically transform agriculture by greatly expanding the number of contexts in which the techniques of precision agriculture may be applied. Inevitably, this next agricultural revolution will generate profound ethical issues: opportunities as well as risks. Clever applications of AI and robotics may allow agriculture to be more sustainable by facilitating more precise applications of water, fertilisers, and herbicides. Robots may take some of the drud... R. Sparrow |
81. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US MidwestEffective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly acr... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan |
82. AI-based Precision Weed Detection and EliminationWeeds are a significant challenge in agriculture, competing with crops for resources and reducing yields. Addressing this issue requires efficient and sustainable weed elimination systems. This paper presents a comprehensive overview of recent advancements in weed elimination system development, focusing on innovative technologies and methodologies. Specifically, it details the development and integration of a weed detection and elimination system based on the CoreXY architecture, implemented... H. Kulhandjian, M. Kulhandjian, D. Rocha, B. Bennett |
83. AgDataBox-IA – Web Application with Artificial Intelligence for Agricultural Data Analysis in Precision AgricultureAgriculture has been continually evolving, incorporating hardware, software, sensors, aerial surveys, soil sampling for chemical, physical, and granulometric analysis (based on sample grids), and microclimatic data, leading to a substantial volume of data. This requires platforms to store, manage, and transform these data into actionable information for decision-making in the field. In this regard, Artificial Intelligence (AI) is the most widely used tool globally to mine and transform vast d... R. Sobjak, C.L. Bazzi, K. Schenatto, W.K. Oliveira, A.E. Menegasso |
84. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane FeedstockPredicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicell... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland |
85. Drought Tolerance Assessment with Statistical and Deep Learning Models on Hyperspectral Images for High-throughput Plant PhenotypingDrought is an important factor that severely restricts blueberry growth, output and adversely impacts the desirable physiologic quality. Considering the challenges posed by climate change and erratic weather patterns, evaluating the drought tolerance of blueberry plants is not only vital for the agricultural industry but also for ensuring a consistent supply of these nutritious berries to consumers. Blueberry plants have a relatively ineffective water regulation mechanism due to their shallow... M. Rahman, S. Busby, A. Sanz-saez, S. Ru, T. Rehman |
86. A High-throughput Phenotyping System Evaluating Salt Stress Tolerance in Kale Plants Cultivated in Aquaponics EnvironmentsMonitoring plant growth in a controlled environment is crucial to make informed decisions for various management practices such as fertilization, weed control, and harvesting. Agronomic, physiological, and architectural traits in kale plants (Brassica oleracea) are important to producers, breeders, and researchers for assessing the performance of the plants under biotic and abiotic stresses. Traditionally, architectural, and morphological traits have been used to monitor plant growth. H... T. Rehman, M. Rahman, E. Ayipio, D. Lukwesa, J. Zheng, D. Wells, H.H. Syed |
87. Algorithm to Estimate Sorghum Grain Number from Panicles Using Images Collected with a Smartphone at Field-scaleAn estimation of on-farm yield before harvest is important to assist farmers on deciding additional input use, time to harvest, and options for end uses of the harvestable product. However, obtaining a rapid assessment of on-farm yield can be challenging, even more for sorghum (Sorghum bicolor L.) crop due to the complexity for accounting for the grain number at field-scale. One alternative to reduce labor is to develop a rapid assessment method employing computer vision and artificial intell... G.N. Nocera santiago, P. Cisdeli magalhães, I. Ciampitti, L. Marziotte |
88. Towards a Digital Peanut Profile Board: a Deep Learning ApproachArtificial intelligence techniques, particularly deep learning, offer promising avenues for revolutionizing object detection and counting algorithms in the context of digital agriculture. The challenges faced by peanut farmers, particularly the precise determination of optimal maturity for digging, have prompted innovative solutions. Traditionally, peanut maturity assessment has relied on the Peanut Maturity Index (PMI), employing a manual classification process with the aid of a peanut profi... M.F. Freire de oliveira, B.V. Ortiz, J.B. Souza, Y. Bao, E. Hanyabui |
89. Utilizing Hyperspectral Field Imagery for Accurate Southern Leaf Blight Severity Grading in CornCrop disease detection using traditional scouting and visual inspection approaches can be laborious and time-consuming. Timely detection of disease and its severity over large spatial regions is critical for minimizing significant yield losses. Hyperspectral imagery has been demonstrated as a useful tool for a broad assessment of crop health. The use of spectral bands from hyperspectral data to predict disease severity and progression has been shown to have the capability of enhancing e... G. Vincent, M. Kudenov, P. Balint-kurti, R. Dean, C.M. Williams |
90. HOPSY: Harvesting Optimization for Production of Strawberry Using Real-time Detection with YOLOv8Optimizing the harvesting process presents a continuous challenge within the strawberry industry, especially during peak seasons when precise labor allocation becomes critical for efficiency and cost-effectiveness. The conventional method for addressing this issue has been hindered by an absence of real-time data regarding yield distribution, resulting in less-than-ideal worker assignments and unnecessary expenditures on labor. In response, a novel, portable, real-time strawberry detection sy... Z. Huang, W. Lee, N. Takkellapati |
91. Optimal Placement of Soil Moisture Sensors in an Irrigated Corn FieldPrecision agricultural practices rely on characterization of spatially and temporally variable soil and crop properties to precisely synchronize inputs (water, fertilizer, etc.) to crop needs; thereby enhancing input use efficiency and farm profitability. Generally, the spatial dependency range for soil water content is shorter near the soil surface compared to deeper depths, suggesting a need for more sampling locations to accurately characterize near-surface soil water content. However, det... D. Mandal, L. Longchamps, R. Khosla |
92. Real-time Seed Mapping Using Direct MethodsSeed distance estimations are critical for planter evaluation and the prediction of planting parameter performance. However, these estimations are typically not conducted in real-time. In this study, we propose a real-time seed mapping approach using cameras and computer vision networks, augmented by a Kalman filter for vehicle state estimation. This process involves the transformation of pixel coordinates into real-world coordinates. We conduct a comparative analysis between these estimates ... A. Sharda, R. Harsha chepally |
93. Incorporating Return on Investment for Profit-driven Management ZonesAdopting site-specific management practices such as profitability zones can help to stabilize long-term profit while also favoring the environment. Profitability maps are used to standardize data by converting variables into economic values ($/ha) for different cropping systems within a field. Thus, profitability maps can be used to define management zones from several years of data and show the regions within a field which are more profitable to invest in for production, or those that can be... A.A. Boatswain jacques, A.B. Diallo, A. Cambouris, E. Lord, E. Fallon |
94. Leveraging UAV-based Hyperspectral Data and Machine Learning Techniques for the Detection of Powderly Mildew in VineyardsThis paper presents the development and validation of machine learning models for the detection of powdery mildew in vineyards. The models are trained and validated using custom datasets obtained from unmanned aerial vehicles (UAVs) equipped with a hyperspectral sensor that can collect images in visible/near-infrared (VNIR) and shortwave infrared (SWIR) wavelengths. The dataset consists of the images of vineyards with marked regions for powdery mildew, meticulously annotated using LabelImg.&n... S. Bhandari, M. Acosta, C. Cordova gonzalez, A. Raheja, A. Sherafat |
95. Combining Remote Sensing and Machine Learning to Estimate Peanut Photosynthetic ParametersThe environmental conditions in which plants are situated lead to changes in their photosynthetic rate. This alteration can be visualized by pigments (Chlorophyll and Carotenoids), causing changes in plant reflectance. The goal of this study was to evaluate the performance of different Machine Learning (ML) algorithms in estimating fluorescence and foliar pigments in irrigated and rainfed peanut production fields. The experiment was conducted in the southeast of Georgia in the United States i... C. Rossi, S.L. Almeida, M.N. Sysskind, L.A. Moreno, A. Felipe dos santos, L. Lacerda, G. Vellidis, C. Pilcon, T. Orlando costa barboza |
96. Using Machine Vision to Build Field Maps of Forage Quality and the Need for Agriculture-specific Machine Vision NetworksMachine vision systems have truly come of age over the past decade. These networks are relatively simple to implement with systems such as YOLOv5 or the more recent YOLOv8. They are also relatively easy and computationally cheap to retrain to a custom data set, allowing for customization of these networks to new object detection and classification tasks. With this ease, it is no surprise that we are seeing an explosion of these networks and their application through all aspects of a... P. Nugent, J. Neupane |
97. Detection of Sorghum Aphids with Advanced Machine VisionSorghum aphid, Melanaphis sorghi (Theobald), became a significant pest concern due to the significant yield losses caused in the sorghum production region. Different management practices, including monitoring and applying insecticides, have been used to manage this invasive pest in sorghum. The most common management strategy consists of visual assessments of aphids on sorghum leaves to determine an economic threshold level to spray. However, because of their rapid reproduction,... I.A. Grijalva teran, B. Spiesman, N. Clark, B. Mccornack |
98. Sparse Coding for Classification Via a Locality Regularizer: with Applications to AgricultureHigh-dimensional data is commonly encountered in various applications, including genomics, as well as image and video processing. Analyzing, computing, and visualizing such data pose significant challenges. Feature extraction methods become crucial in addressing these challenges by obtaining compressed representations that are suitable for analysis and downstream tasks. One effective technique along these lines is sparse coding, which involves representing data as a sparse linear combination ... A. Tasissa, L. Li, J.M. Murphy |
99. Spatial Predictive Modeling to Quantify Soybean Seed Quality Using Remote Sensing and Machine LearningIn recent years, the advancement of artificial intelligence technologies combined with satellite technology is revolutionized agriculture through the development of algorithms that help producers become more sustainable. This could improve the conditions of farmers not only by maximizing their production and minimizing environmental impact but also due to better economic benefits by allowing them to access high-value-added markets. Furthermore, the use of predictive tools that could improve t... C. Hernandez, P. Kyveryga, A. Correndo, A. Prestholt, I. Ciampitti |
100. Obstacle-aware UAV Flight Planning for Agricultural ApplicationsThe use of unmanned aerial vehicles (UAVs) has emerged as one of the most important transformational tools in modern agriculture, offering unprecedented opportunities for crop monitoring, management, and optimization. To ensure effective and safe navigation in agricultural environments, robust obstacle avoidance capabilities are required to mitigate collision risks and to ensure efficient operations. Mission planners for UAVs are typically responsible for verifying that the vehicle is followi... K. Joseph, S. Pitla, V. Muvva |
101. Supervised Hyperspectral Band Selection Using Texture Features for Classification of Citrus Leaf Diseases with YOLOv8Citrus greening disease (HLB), a disease caused by bacteria of the Candidatus Liberibacter group, is characterized by blotchy leaves and smaller fruits. Causing both premature fruit drop and eventual tree death, HLB is a novel and significant threat to the Florida citrus industry. Citrus canker is another serious disease caused by the bacterium Xanthomonas citri subsp. citri (syn. X. axonopodis pv. citri) and causes economic losses for growers from fruit drops and blemishes. Citrus cank... Q. Frederick, T. Burks, P.K. Yadav, M. Dewdney, J. Qin, M. Kim |
102. A Growth Stage Centric Approach to Field Scale Corn Yield Estimation by Leveraging Machine Learning Methods from Multimodal DataField scale yield estimation is labor-intensive, typically limited to a few samples in a given field, and often happens too late to inform any in-season agronomic treatments. In this study, we used meteorological data including growing degree days (GDD), photosynthetic active radiation (PAR), and rolling average of rainfall combined with hybrid relative maturity, organic matter, and weekly growth stage information from three small-plot research locati... L. Waltz, S. Katari, S. Khanal, T. Dill, C. Porter, O. Ortez, L. Lindsey, A. Nandi |
103. RMAPs: an Integrated Tool to Delimitate Homogeneous Management ZonesManagement zones are one of the most studied methods in precision agriculture to optimize crop yield from the soil, plant, management, and climate input parameters. We present Rmaps, an R package that integrates soil and crop yield spatial variability using geostatistical methods and one-hidden-layer perceptron (OHLP) to identify how input parameters influence crop yield and delimitate homogenous zones. From georeferenced data of soil, plant, management, climate, and crop yield parameters, Rm... E. Erazo, C. Mosquera, O. Ochoa |
104. AI Enabled Targeted Robotic Weed ManagementIn contemporary agriculture, effective weed management presents a considerable challenge necessitating innovative solutions. Traditional weed control methods often rely on the indiscriminate application of broad-spectrum herbicides, giving rise to environmental concerns and unintended crop damage. Our research addresses this challenge by introducing an innovative AI-enabled robotic system designed to identify and selectively target weeds in real-time. Utilizing the advanced Machine Learning t... A. Balabantaray, S. Pitla |
105. AI-enabled 3D Vision System for Rapid and Accurate Tree Trunk Detection and Diameter EstimationHuanglongbing (HLB) is the major threat to citrus production in Florida. Imidacloprid and oxytetracycline injections were proven to be effective in controlling HLB. The total amount of imidacloprid and oxytetracycline needs to be injected for the tree depending on the trunk diameter. Therefore, precisely measuring trunk diameter is important to effectively control the HLB. However, manually injecting imidacloprid or oxytetracycline and measuring the trunk diameter is time-consuming and labor-... C. Zhou, Y. Ampatzidis |
106. Active Learning-based Measurements Prediction in Sparsely Observed Agricultural FieldsThe sustainability of farming methods relies on the quality of soil health. Rich soil supplies vital nutrients to plants. The soil structure and aggregation possess crucial physical attributes that facilitate the infiltration of water and air, as well as enable roots to explore. Long-term and extensive monitoring of soil data is crucial for obtaining important information into the water dynamics of the land surface. Soil moisture dynamics play a critical role in the hydrothermal process that ... D. Agarwal, A. Tharzeen, B. Natarajan |
107. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and VisionAdvancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collec... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi |
108. In-Field and Loading Crop: A Machine Learning Approach to Classify Machine Harvesting Operating ModeThis paper addresses the complex issue of classifying mode of operation (active, idle, stationary unloading, on-the-go unloading, turning) and coordinating agricultural machinery. Agricultural machinery operators must operate within a limited time window to optimize operational efficiency and reduce costs. Existing algorithms for classifying machinery operating modes often rely on heuristic methods. Examples include rules conditioned on machine speed, bearing angle and operational t... D. Buckmaster, J. Krogmeier, J. Evans, Y. Zhang, M. Glavin, D. Byrne, S.J. Harkin |
109. Estimating Real-time Soil Water Content (SWC) in Corn and Soybean Fields Using Machine Learning Models, Proximal Remote Sensing, and Weather DataSoil Water Content (SWC) is crucial for precise irrigation management, especially in center-pivot systems. Real-time estimation of SWC is vital for scheduling irrigation to prevent overwatering or underwatering. Proper irrigation yields benefits such as improved water efficiency, enhanced crop yield and quality, minimized environmental impact, optimized labor and energy costs, and improved soil health. Various in-situ techniques, such as Time-domain reflectometry (TDR), frequency-do... N. Chamara, Y. Ge, F. Bai |
110. Enhancing Seeding Efficiency: Evaluating Row Cleaners with Computer Vision in Precision AgricultureIn precision agriculture, the effective sowing of seeds is crucial but often hindered by challenges like hair pinning, low soil temperatures, and heavy residue on the soil surface. To address these issues, row cleaners are employed to clear the path for seeder opener discs, ensuring a clean, uniform trench for seed placement. This study examines the performance of various row cleaner models and introduces a novel method for their automatic, quantitative evaluation using computer vision techno... F. Sidharth, A. Sharda, B.G. Berretta |
111. Cotton Yield Estimation Using High-resolution Satellite Imagery Obtained from Planet SkySatSatellite images have been used to monitor and estimate crop yield. Over the years, significant improvements on spatial resolution have been made where ortho images can be generated at 30-centimeter resolution. In this study, we wanted to explore the potential use of Planet SKYSAT satellite system for cotton yield predictions. This system provided imagery data at 50 centimeters resolution, and we collected data 14 times during the season. The data were collected from two different cotton... M. Bhandari |
112. AIR-N: AI-Enabled Robotic Precision Nitrogen Management PlatformThe AI-Enabled Robotic Nitrogen Management (AIR-N) system is a versatile, cloud-based platform designed for precision nitrogen management in agriculture, targeting the reduction of nitrous oxide emissions as emphasized by the EPA. This end-to-end integrated system is adaptable to various cloud services, enhancing its applicability across different farming environments. AIR-N's framework consists of three primary components: a sensing layer for gathering data, a cloud layer where AI and ma... A. Kalra, S. Pitla, J.D. Luck |
113. Bird Welfare and Comfort in Poultry Coops Through Computations and AIBird welfare and comfort is very important inside poultry coops during transportation, especially during summer and winter months. The microenvironment inside a poultry coop resulting from hot/cold temperatures, relative humidity and heat production leads to complex scenarios affecting the bird welfare. The enthalpy comfort index (ECI) that relates to temperature, relative humidity was calculated to evaluate the poultry coop welfare that corresponds to bird welfare conditions (comfort; ... R. Pidaparti, A. Moghadham, H. Thippareddi |
114. Determining Desirable Swine Traits that Correlate to High Carcass Grades for Artificial Intelligence PredictionsWith the global population continuing to grow, there has been an increased stress applied to the agriculture industry to improve efficiency and yield. To achieve this goal within the cattle industry, selection and reproductive decisions have been lucrative aspects, both genetically and fiscally. Breeding animal selection impacts farms through passing on favorable market, reproductive, and temperament traits. The cattle industry has experienced genetic advancement due to the flexibility of art... A.N. Spina, J.P. Fulton, S.A. Shearer, T. Berger-wolf, D. Drewry |
115. 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 |
116. Premier Strategy Consulting - Sponsor Presentation... C. Zhu |
117. Advanced Classification of Beetle Doppelgängers Using Siamese Neural Networks and Imaging TechniquesThe precise identification of beetle species, especially those that have similar macrostructure and physical characteristics, is a challenging task in the field of entomology. The term "Beetle Doppelgängers" refers to species that exhibit almost indistinguishable macrostructural characteristics, which can complicate tasks in ecological studies, conservation efforts, and pest management. The core issue resides in their striking similarity, frequently confusing both experts and a... P.R. Armstrong, L.O. Pordesimo, K. Siliveru, A.R. Gerken, R.O. Serfa juan |
118. Spectral Imaging Deep Learning Mapper for Precision AgricultureWith the growing variety of RGB cameras, spectral sensors, and platforms like field robots or unmanned aerial vehicles (UAV) in precision agriculture, there is a demand for straightforward utilization of collected field data. In recent years, deep learning has gained significant attention and delivered impressive results in the realm of computer vision tasks, such as semantic segmentation. These models have also found extensive applications in research related to precision agriculture and spe... L. Thomas, B. Jakimow, A. Janz, P. Hostert, A. Lajunen |
119. Predicting Soybean Yield Using Remote Sensing and a Machine Learning ModelSoybean (Glycine max L.), a nutrient-rich legume crop, is an important resource for both livestock feed and human dietary needs. Accurate preharvest yield prediction of soybeans can help optimize harvesting strategies, enhance profitability, and improve sustainability. Soybean yield estimation is inherently complex because yield is influenced by many factors including growth patterns, varying crop physiological traits, soil properties, within-field variability, and weather conditions. The obj... M. Gardezi, O. Walsh, D. Joshi, S. Kumari, D.E. Clay, J. Rathore |
120. Using Informative Bayesian Priors and On-farm Experimentation to Predict Optimal Site-specific Nitrogen RatesMost U.S. Corn Belt states now recommend the Maximum Return to Nitrogen (MRTN) method for determining optimal nitrogen rates, which is based on 15 years of on-farm yield response to nitrogen trials. The MRTN method recommends a uniform rate for a region of a state. This study combines Illinois MRTN data, Bayesian methods, and on-farm experimentation from the Data Intensive Farm Management (DIFM) project to provide site-specific nitrogen recommendations. On-farm trials are now being used to pr... W. Brorsen, D. Poursina, C. Patterson, T. Mieno, B. Edge, E.D. Nafziger |
121. 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 ... J. Cesario pinto, L. Thompson, N. Mueller, T. Mieno, L. Puntel, P. Paccioretti, G. Balboa |
122. The Impact of Row Unit Position on Planter Toolbar on Corn Crop Development: an Experimental StudyPrecision planting techniques are essential to grow corn successfully. Monitoring planter speed, row-unit bounce, and gauge-wheel load ensures high-quality seeding. Vertical vibration during planting can impede seed metering and delivery, causing planting variability. Row unit vibration increases with planting speed and can lead to spatial variability in planting. Therefore, the goals of this study were to 1) understand the influence of row unit location on its vertical vibration; and 2) comp... J. Peiretti, A. Sharda, S. Badua |
123. Enhancing On-farm Rice Yields, Water Productivity, and Profitability Through Alternate Wetting and Drying Technology in Dry Zones of West AfricaIrrigated rice farming is crucial for meeting the growing rice demand and ensuring global food security. Yet, its substantial water demand poses a significant challenge in light of increasing water scarcity. Alternate wetting and drying irrigation (AWD), one of the most widely advocated water-saving technologies, was recently introduced as a prospective solution in the semi-arid zones of West Africa. However, it remains debatable whether AWD can achieve the multiple goals of saving water whil... Y.J. Johnson, M. Becker, E.R. Dossou-yovo, K. Saito |
124. Analysis of Yield Gaps in Sub-Saharan African Cereal Production SystemsFood production in sub-Saharan Africa (SSA) is one of the lowest and keeps declining across farmers’ fields season after season (Assefa et al., 2020; F Affholder, 2013). Yield gaps in cereal cropping systems have been reported by many researchers, attesting to the existence of huge variability in production levels of cereals such as corn, wheat, sorghum, rice and millet. across SSA. It is still unclear whether the yield gaps are similar in size or driven by similar factors across differ... E. Odoom, K.A. Frimpong, S. Phillips |
125. Optimizing Experimental Design for Determining Economic Nitrogen Levels: Insights on the Use of Monte Carlo SimulationsThe determination of economic nitrogen levels is a pivotal element in the quest for sustainable agricultural practices. Designing experiments to accurately identify these levels, especially in contexts constrained by limited plot availability, poses a significant challenge. In response to these challenges, this study endeavors to demonstrate an approach to optimize the experimental design for identifying economic nitrogen levels, even under such constraints. We employed statistical... C. Matavel, A. Meyer-aurich, H. Piepho |
126. Effective Furrow Closing Systems for Consistent Corn Seed PlacementFarmers face a constant challenge when choosing the appropriate planter setup due to the variability of cropping systems under no-till. Effective performance of the planter's closing wheels can reduce errors from previous components that affect seedbed formation in the furrow. Effective seed-to-soil contact during planting is essential for optimal seed emergence and overall crop stand, with the closing wheels playing a pivotal role in this process. Producers have a range of closing wheels... J. Peiretti, B. Gigena, S. Badua, A. Sharda |
127. Assessment of Soil Spatial Properties and Variability Using a Portable VIS-NIRS Soil Probe for On-farm Precision ExperimentationAssessing the spatial variability of soil properties represents an important issue for on-farm sustainable management owing to high cost of sampling densities. Actual methods of soil properties measurement are based on conventional soil sampling of one sample per ha, followed by laboratory analysis, requiring many soil extraction processes and harmful chemicals. This conventional laboratory analysis does not allow exploring spatial variation of soil properties at desired fine spatial scale. T... A. Cambouris, M. Duchemin, E. Lord, N. Ziadi, B. Javed, J.D. Nze memiaghe, D.A. Ramirez-gonzalez |
128. Operationalization of On-farm Experimentation in African Cereal Smallholder Farming SystemsPast efforts have concentrated on linear or top-down approaches in delivering precision nutrient management (PNM) practices to smallholder farmers. These deliberate attempts at increasing adoption of PNM practices have not yielded the expected outcomes, that is, increased productivity and nutrient use efficiency, at scale. This is because technologies generated by scientists with minimal farmer involvement often are not well tailored to the attendant agro-ecological, socio-economic, and cultu... I. Adolwa, S. Phillips, B.A. Akorede, A.A. Suleiman, T. Murrell, S. Zingore |
129. Harnessing Farmers’, Researchers’ and Other Stakeholders’ Knowledge and Experiences to Create Shared Value from On-farm Experimentation: Lessons from KenyaAchieving greater sustainability in farm productivity is a major challenge facing smallholder farmers in Kenya. Existing technologies have not solved the challenges around declining productivity because they are one-size-fits-all that doesn’t account for the diverse smallholder contexts. A study was carried out in Kenya by a multi-disciplinary team to assess the value of On-Farm Experimentation (OFE) to tailor technologies to local conditions. The OFE process begun with identification o... J. Muthamia, I. Adolwa, J. Mutegi, S. Zingore, S. Phillips |
130. Determining Site-Specific Soybean Optimal Seeding Rate Using On-Farm Precision ExperimentationTen on-farm precision experiments were conducted in Nebraska during 2018 – 2022 to address the following: i) determine the Economic Optimal Seeding Rates (EOSR), ii) identify the most important site-specific variables influencing the optimal seeding rates for soybeans. Seeding rates ranged from 200,000 to 440,000 seeds ha-1, and treatments were randomized and replicated in blocks across the entire field. The study was implemented using a variable rate prescription. ... M.M. Dalla betta, L. Puntel, L. Thompson, T. Mieno, J.D. Luck, N. Cafaro la menza, P. Paccioretti |
131. Creating Value from On-farm Research: Efields Data Workflow and Management Successes and ChallengesFarm operations today generate a large amount of data that can be difficult to properly manage. This challenge is further compounded when conducting on-farm research. The Ohio State University eFields program partners with farmers to conduct on-farm research and share results in a timely manner. Since 2017, the team has conducted and shared 987 trials across Ohio with the annual number of trials increasing from 45 to 292. This rapid increase has required development of a data workflow that st... J.P. Fulton, D. Wilson, R. Tietje, E. Hawkins |
132. Evaluating Different Strategies to Analyze On-farm Precision Nitrogen Trial DataOn-farm trials are being conducted by more and more researchers and farmers. On-farm trials are very different to traditional small plot experiments due to the existence of significant within-field variability in soil-landscape conditions. Traditional statistical techniques like analysis of variance (ANOVA) are commonly adopted for on-farm trial analysis to evaluate overall performance of different treatments, assuming uniform environmental and management factors within a field. As a result, ... K. Mizuta, Y. Miao, J. Lu, R.P. Negrini |
133. Influence of Potassium Variability on Soybean YieldDue to its role as a plant essential nutrient, Potassium (K) serves as a fundamental component for plant growth. Soybeans are heavily reliant upon this nutrient for root growth and the production of pods, so much so that after nitrogen, potassium is the second most in-demand nutrient. Much of the overall soybean crop grown in Oklahoma is not managed with the fertility of K directly in mind. However, as the potential and expectation for greater yield increases, so does interest from produ... J. Derrick, S. Akin, R. Sharry, B. Arnall |
134. All for One and One for All: a Simulation Assessment of the Economic Value of Large-scale On-farm Experiment NetworkWhile on-farm experiments offer invaluable insights for precision management decisions, their scope is usually confined to the specific conditions of individual farms and years, which limits the derivation of more broad and reliable decisions. To address this limitation, aggregating data from numerous farms of various crop growth conditions into a comprehensive dataset appears promising. However, the quantifiable value of this experiment network remains elusive, despite the common agreement o... X. Li |
135. 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 chlo... F. Pereira de souza, R.P. Negrini, H. Tao |
136. On-farm Experimentation Case Study in Brazil: Evaluation of Soybean Seeding Rate Using Resources Available at the FarmIn order to maximize grain yield in soybean (Glycine max [L.] Merr.) it is necessary that the plant population is correctly defined. Production environments differ spatially, and cultivar holders suggest plant populations across macroregions and in broad ranges. Refinements of planting seasons and populations are carried out through tests on many properties, often costly and sometimes unrepresentative of most fields. Tools for managing spatial variability are ways to conduct mor... M. Rodrigues alves franchi, I. Molina cyrineu, F. Kagami taira, L. Hunhoff, L.M. Gimenez |
137. Driving Growth Through Precision Agriculture: the Evolution of the Nebraska On-farm Research NetworkThe Nebraska On-Farm Research Network (NOFRN), allows farmers to answer production, profitability and sustainability questions in their own field. The University of Nebraska (USA) sponsors the NOFRN and provides technical support in the experimental design, execution, data analysis and results dissemination. In recent years, precision agriculture technologies have expanded network capabilities through an increasing number of experiments and provided new avenues for data analyses. The goal ... G. Balboa, B. Tobaldo, T. Lexow, J.D. Luck |
138. Symposium Welcome and Introductions... J. Lowenberg-deboer |
139. How Does an Autonomous Tractor See the World... G. Bansal |
140. Transforming Row Crop Agriculture: Harnessing Computer Vision and AI for Automation and Autonomy... A. Sharda |
141. Swarm Farming is the Future... C. Rupp |
142. Evolving Nexus of Academia, Industry, and Government to Advance and Realize the Benefits of Robotics in Crop Production Agriculture... E.M. Barnes, M. Scott, S.A. Shearer |
143. Machine Vision, AI, and Robotics in Specialty Crop Production... M. Karkee |
144. Can AI and Automation Transform Specialty Crop Production?... Y. Ampatzidis |
145. Using AI to Estimate Vineyards and Vegetables Vigour and Yield... S. Fountas |
146. I Call Shotgun: Uncovering Human-System/Robot Gaps in Emerging Technologies... Y. Salzer |
147. Stakeholder Inclusion for Responsible Robotics: Who, How, and Why?... D. Rose |
148. Field Crop Robots - Adoption and Farm Level Economics... M. Gandorfer |
149. Development of a Multispectral Vision-based Automated Sweetpotato Grading SystemQuality evaluation and grading of sweetpotatoes is a manual operation that requires significant labor input. Machine vision technology offers a promising solution for automated sweetpotato grading and sorting. Although color imaging is widely used for quality evaluation of various horticultural commodities, a multispectral vision technique that acquires color and near-infrared (NIR) images simultaneously is a potentially more effective modality for fruit grading, especially for defects, while... J. Xu, Y. Lu |