Proceedings
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1. Variability In Wheat Crop Production Based On Management Zones In Humid Pampas Region, ArgentinaCrop productivity within fields is heterogeneous and it responds to the variation in crop management patterns, and in previous, random, and natural crop management factors. The methodologies for the delimitation of management zones (MZ) within production fields differ based on their application objectives. The objectives... M. L, M. Diaz-zorita, P. Mercuri |
2. Development And Application Of Gully Erosion Components Within The USDA Annagnps Watershed Model For Precision ConservationA watershed scale assessment of the effect of conservation practices on the environment is critical when recommending conservation management practices to agricultural producers. The identification of all sources of sediment and subsequent tracking of the movement of sediment downstream is a necessary part of this assessment including the often overlooked contributions from gully erosion sources. Pollutant loading allocations established with comprehensive studies of all sediment sources... R.L. Bingner, R.R. Wells, F.D. Theurer |
3. Assessing the Potential of an Algorithm Based On Mean Climatic Data to Predict Wheat YieldIn crop yield prediction, the unobserved future weather remains the key point of predictions. Since weather forecasts are limited in time, a large amount of information may come from the analysis of past weather data. Mean data over the past years and stochastically generated data are two possible ways to compensate the lack of future data. This research aims to demonstrate that it is possible to predict... F. Vancutsem, V. Leemans, S. Ferrandis vallterra, B. Bodson, J. Destain, M. Destain, B. Dumont |
4. Bayesian Methods for Predicting LAI and Soil MoistureCrop models describe the growth and development of a crop interacting with soil, climate, and management... M. Majdi, D. Benjamin, D. Marie-france |
5. Applications for Precision Agriculture: the Italian Experience of SIRIUS ProjectThis paper reports the results of the project SIRIUS (Sustainable Irrigation water management and River-basin... P. Nino, S. Vanino, F. Lupia, F. Altobelli, F. Vuolo, I. Namdarian, C. De michele |
6. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images... X. Song, C. Zhao, L. Chen, W. Huang, B. Cui |
7. Improvement Precision Agricultural Communication Schema agroXML Based on Multi-Agents System's Deliberation and Decision Making Processes... A. Pentjuðs, A. Gailums |
8. Brazilian Precision Agriculture Research NetworkThe adoption of adequate technologies for food, biomass and fiber production can increase yield and quality and also reduce environmental impact through an efficient input application. Precision agriculture is the way to decisively contribute with efficient production with environment protection in Brazil. Based on this, recently Embrapa established the Brazilian Precision... J.D. Naime, L.R. Queiros, A.V. Resende, M.D. Vilela, L.H. Bassoi, N.B. Perez, A.C. Bernardi, R.Y. Inamasu |
9. Adoption and Tendencies of Precision Agriculture Technologies in the Tocantins State, BrazilAlthough precision agriculture is widely used throughout Brazilian crop production, it has not been used to increase the efficiency use of agricultural inputs. Besides, technologies available have not been... L. Bortolon, E. Borghi, A. Luchiari junior, E.S. Bortolon, A.A. Freitas, R.Y. Inamasu, J.C. Avanzi |
10. Evaluating Spectral Measures Derived From Airborne Multispectral Imagery for Detecting Cotton Root RotCotton root rot, caused by the soilborne fungus Phymatotrichopsis omnivore, is one of the most destructive plant diseases occurring... C. Yang, G.N. Odvody, C.J. Fernandez, J.A. Landivar, R.L. Nichols |
11. Remote Sensing of Nitrogen and Water Status on Boston Lettuce Transplants in a Greenhouse EnvironmentRemote sensing is the stand-off collection through the use of a variety of devices for gathering information on a given object or area. Applied as a warning tool in plant stock production, it is expected to help in the achievement of better, more uniform and more productive organic cropping systems. Remote sensing of vegetation targets can be achieved from the... N. Tremblay, P. Vigneault, M.Y. Bouroubi, M. Dorais, G.P. Gianquinto, M. Tempesta |
12. Adoption Level Of Precision Agriculture For Brazilian Farmers - 2011/12 Crop YearAlthough Precision Agriculture (PA) concepts and technologies are widespread in Brazil, its application still little used in some important crop production regions. The purpose of this study was to survey the current adoption level of PA by printed and online questionnaire. We started making a specific questionnaire to farmers and PA service companies using some technology related to PA. The questionnaires were developed based on the methodology of Whipker and Akridge (2009),... E. Borghi, A. Luchiari junior, L. Bortolon, E.S. Bortolon, R.Y. Inamasu, A.C. Bernardi, J.C. Avanzi |
13. 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 hyperspectral... T. Dong, J. Shang, J. Meng, J. Liu |
14. Evaluating Different Nitrogen Management Strategies For The Intensive Wheat-Maize System In North China PlainThe sustainable agricultural development involves both environmental challenges and production goals to meet growing food demand. However, excessive nitrogen (N) applications are threatening the sustainability of intensive agriculture in the North China Plain (NCP). Improved N management should result in greater N use efficiency (NUE) and producer profit while reducing the risk of environmental contamination. Therefore, developing and disseminating feasible N management strategies... Q. Cao, Y. Miao, G. Feng, F. Li, B. Liu, X. Gao, Y. Liu |
15. Nitrogen Fertilisation Recommendations : Could They Be Improved Using Stochastically Generated Climates In Conjunction With Crop Models ?In the context of precision nitrogen (N) management, to ensure that the yield potential could be reached each year, farmers have too often applied quantities of fertilizers much larger than what was strictly required. However, since 2002, the Belgian Government transposed the European Nitrate Directive 91/676/EEC in the Belgian law, with the aim to maintain the productivity and the revenue of Belgian's farmers while reducing the environmental impact of excessive N management... B. Basso, J. Destain, B. Bodson, M. Destain, B. Dumont |
16. Design Of ECU Monitoring System For Agricultural Vehicle Based On ISO 11783International standard for implementation of electronic control unit (ECU) in agricultural tractors has been requirement for inter-operation compatibility of various agricultural vehicles. The ISO 11783 standard is basically based on communication technology designated using the controller area network (CAN), it is typical standard technology for implementation of ECU in agricultural vehicle. CAN bus Communication system was developed to the distribution control of ECUs to... W. Yang , S. Kim, J. Moon, D. Kim |
17. Estimation Of Nitrogen And Chlorophyll Content In Wheat Crop Using Hand Held SensorsA Field experiment was conducted to estimate crop nitrogen (N) status and chlorophyll content in wheat crop by using chlorophyll content meter(Apogee’s CCM-200) and N-Tester® (Make YARA International). The experiment was conducted by sowing university recommended wheat variety viz. PBW 550 with 5 nitrogen levels i.e. 0, 30, 60, 90, 120 & 150 kg N/ha. It was found that at tillering stage when nitrogen rates were increased from 0 to 150 kg ha-1 , the... M.S. Makkar, A. Kaul, R. Kumar, A. Sharma, B.S. Sekhon, C.S. Pannu |
18. Precision Nutrient Management For Enhancing The Yield Of Groundnut In Peninsular IndiaGroundnut is an important oil seed crop grown in an area of around 8 lakh hectares in Karnataka state of India under rainfed conditions. In these situations farmers applied inadequate fertilizer without knowing the initial nutrient status of the soil which resulted in low nutrient use efficiency that intern lead to low productivity of groundnut in these areas. Soil fertility deterioration due to... M. Giriyappa, T. Sheshadri, D. Hanumanthappa, M. Shankar, S.B. Salimath, T. Rudramuni, N. Raju, N. Devakumar, G. Mallikaarjuna, M.T. Malagi, S. Jangandi |
19. sUAVS Technology For Better Monitoring Crop Status For Winter CanolaThe small-unmanned aircraft vehicles (sUAVS) are currently gaining more popularity in agriculture with uses including identification of weeds and crop production issues, diagnosing nutrient deficiencies, detection of chemical drift, scouting for pests, identification of biotic or abiotic stresses, and prediction of biomass and yield. Research information on the use of sUAVS have been published and conducted in crops such as rice, wheat, and corn, but the development of... I.A. Ciampitti, K. Shroyer, V. Prasad, A. Sharda, M.J. Stamm, H. Wang, K. Price, D. Mangus |
20. Detection of Nitrogen Stress on Winter Wheat by Multispectral Machine VisionHand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for detecting... M. Destain, V. Leemans, G. Marlier, J. Goffart, B. Bodson, B. Mercatoris, F. Gritten |
21. Estimating Environmental Systems Using Iterated Sigma Point Techniques: a Biomass Substrate Hypothetical SystemThis paper addresses the problem of biomass substrate hypothetical system estimation using sigma points kalman filter (SPKF) methods. Various conventional and state-of-theart state estimation methods are compared for the estimation performance, namely the unscented Kalman filter(UKF), the central difference Kalman filter (CDKF), the square-root unscented Kalman filter (SRUKF), the square-root central difference Kalman filter (SRCDKF), the iterated unscented Kalman filter (IUKF), the iterated central... I. Baklouti, M. Mansouri, M. Destain, A. Hamida |
22. In-field Plant Phenotyping Using Multi-view Reconstruction: an Investigation in EggplantRapid methods for plant phenotyping are a growing need in agricultural research to help accelerate improvements in crop performance in order to facilitate more efficient utilization of plant genome sequences and the corresponding advancements in associated methods of genetic improvement. Manual plant phenotyping is time-consuming, laborious, frequently subjective, and often destructive. There is a need for building field-deployable systems with advanced sensors that have both high-speed and high-performance... T. Nguyen, D. Slaughter, B. Townsley, L. Carriedo, J. Maloof, N. Sinha |
23. Spatial-temporal Evaluation of Plant Phenotypic Traits Via Imagery Collected by Unmanned Aerial Systems (UAS)Unmanned aerial systems (UAS) and a stereovision approach were implemented to generate a 3D reconstruction of the top of the canopy. The 3D reconstruction or CSM (crop surface model) was utilized to evaluate biophysical parameters for both spatial- and temporal-scales. The main goal of the project was to evaluate sUAVs technology to assist plant height and biomass estimation. The main outcome of this process was to utilize CSMs to gain insights in the spatial-temporal dynamic of plants within... S. Varela, G. Balboa, V. Prasad, T. Griffin, I. Ciampitti, A. Ferguson |
24. Mapping Spatial Production Stability in Integrated Crop and Pasture Systems: Towards Zonal Management That Accounts for Both Yield and Livestock-landscape Interactions.Precision farming technologies are now widely applied within Australian cropping systems. However, the use of spatial monitoring technologies to investigate livestock and pasture interactions in mixed farming systems remains largely unexplored. Spatio-temporal patterns of grain yield and pasture biomass production were monitored over a four-year period on two Australian mixed farms, one in the south-west of Western Australia and the other in south-east Australia. A production stability index was... P. Mcentee, S. Bennett, M. Trotter, R. Belford, J. Harper |
25. Field Evaluation of a Variable-rate Aerial Application SystemVariable rate aerial application systems are becoming more readily available; however, aerial applicators typically only use the systems for constant rate application of materials, allowing the systems to compensate for upwind and downwind ground speed variations. Much of the resistance to variable rate application system adoption pertains to applicator’s trust in the systems to turn on and off automatically as desired. If an application system operating in an automatic mode were... D.E. Martin, C. Yang |
26. Quo Vadis Precision FarmingThe agriculture sector is a unique sector due to its strategic importance for both citizens and economy which, ideally, should make the whole sector a network of interacting organizations. There is an increasing tension, the like of which is not experienced in any other sector, between the requirements to assure full safety and keep costs under control, but also assure the long-term strategic interests of Europe and worldwide. In that sense, agricultural production influences, and is influenced... K. Charvat, T. Reznik, V. Lukas, K. Charvat jr., S. Horakova, M. Splichal, M. Kepka |
27. Spatial-temporal Evaluation of Plant Phenotypic Traits Via Imagery Collected by Unmanned Aerial Systems (UAS)Unmanned aerial systems (UAS) and a stereovision approach were implemented to generate a 3D reconstruction of the top of the canopy. The 3D reconstruction or CSM (crop surface model) was utilized to evaluate biophysical parameters for both spatial- and temporal-scales. The main goal of the project was to evaluate sUAVs technology to assist plant height and biomass estimation. The main outcome of this process was to utilize CSMs to gain insights in the spatial-temporal dynamic of plants within... S. Varela, G. Balboa, V. Prasad, T. Griffin, I. Ciampitti, A. Ferguson |
28. Sources of Information to Delineate Management Zones for CottonCotton in Brazil is an input-intensive crop. Due to its cultivation in large fields, the spatial variability takes an important role in the management actions. Yield maps are a prime information to guide site-specific practices including delineation of management zones (MZ), but its adoption still faces big challenges. Other information such as historical satellite imagery or soil electrical conductivity might help delineating MZ as well as predicting crop performance. The objective of this work... R.G. Trevisan, M.T. Eitelwein, A.F. Colaço, J.P. Molin |
29. Integrated Approach to Site-specific Soil Fertility ManagementIn precision agriculture the lack of affordable methods for mapping relevant soil attributes is a fundamental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor |
30. High Resolution Vegetation Mapping with a Novel Compact Hyperspectral Camera SystemThe COSI-system is a novel compact hyperspectral imaging solution designed for small remotely piloted aircraft systems (RPAS). It is designed to supply accurate action and information maps related to the crop status and health for precision agricultural applications. The COSI-Cam makes use of a thin film hyperspectral filter technology which is deposited onto an image sensor chip resulting in a compact and lightweight instrument design. This paper reports on the agricultural monitoring... B. Delauré, P. Baeck, J. Blommaert, S. Delalieux, S. Livens, A. Sima, M. Boonen, J. Goffart, G. Jacquemin, D. Nuyttens |
31. Melon Classification and Segementation Using Low Cost Remote Sensing Data DronesObject recognition represents currently one of the most developing and challenging areas of the Computer Vision. This work presents a systematic study of various relevant parameters and approaches allowing semi-automatic or automatic object detection, applied onto a study case of melons on the field to be counted. In addition it is of a cardinal interest to obtain the quantitative information about performance of the algorithm in terms of metrics the suitability whereof is determined by the final... T. Zhao, Y. Chen, J. Franzen, J. Gonzalez, Q. Yang |
32. On-the-go Measurements of pH in Tropical SoilThe objective of this study was to assess the performance of a mobile sensor platform with ion-selective antimony electrodes (ISE) to determine pH on-the-go in a Brazilian tropical soil. The field experiments were carried out in a Cambisol in Piracicaba-SP, Brazil. To create pH variability, increasing doses (0, 1, 3, 5, 7 and 9 Mg ha-1) of lime were added on the experimental plots (25 x 10 m) one year before the data acquisitions. To estimate soil pH levels we used a Mobile Sensor Platform... M.T. Eitelwein, R.G. Trevisan, A.F. Colaço, M.R. Vargas, J.P. Molin |
33. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPTAgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy |
34. Liquid Flow Control Requirements for Crop Canopy Sensor-Based N Management in Corn: A Project SENSE Case StudyWhile on-farm adoption of crop canopy sensors for directing in-season nitrogen (N) application has been slow, research focused on these systems has been significant for decades. Much emphasis has been placed on developing and testing algorithms based on sensor output to predict N needs, but little information has been published regarding liquid flow control requirements on equipment used in conjunction with these sensing systems. Addition of a sensor-based system to a standard spray rate controller... J. Luck, J. Parrish, L. Thompson, B. Krienke, K. Glewen, R.B. Ferguson |
35. Thermal Characterization and Spatial Analysis of Water Stress in Cotton (Gossypium Hirsutum L.) and Phytochemical Composition Related to Water Stress in Soybean (Glycine Max)Studies were designed to explore spatial relationships of water and/or heat stress in cotton and soybeans and to assess factors that may influence yield potential. Investigations focused on detecting the onset of water/heat stress in row crops using thermal and multispectral imagery with ancillary physicochemical data such as soil moisture status and photosynthetic pigment concentrations. One cotton field with gradations in soil texture showed distinct patterns in thermal imagery, matching patterns... S.J. Thomson, S.L. Defauw, P.J. English, J.E. Hanks, D.K. Fisher, P.N. Foster, P.V. Zimba |
36. Developing an Integrated Approach for Estimation of Soil Available Nutrient Content Using the Modified WOFOST Model and Time-Series Multispectral UAV ObservationsSoil available nutrient (SAN) plays an important role in crop growth, yield formation, and plant-soil-atmosphere system exchange. Nitrogen (N), phosphorus (P) and potassium (K) are recognized as three primary nutrients in crop production. Accurate and timely information on SAN conditions at key crop growth stages is important for developing beneficial management practices. While traditional field sampling can obtain reliable information for limited number of sites, it is infeasible for spatially... Z. Cheng, J. Meng, J. Shang, J. Liu, B. Qian, Q. Jing |
37. The Influence of Calf’s Sex on Total Milk Yield and Its Constituents of Dairy CowsThe objective of the present work was to evaluate the influence of the sex of the calf on total milk yield and its constituents of Holstein-Friesian dairy cows. The Holstein Livestock Breeders Association of Minas Gerais provided data collected over the years from 2000 to 2016 from 127 dairy farms located in the state of Minas Gerais – Brazil. The data set analyzed contained 61747 observations of Holstein-Friesian animals that calved female (n = 28903) or male (n = 32844) calf. Fat, protein,... G.M. Dallago, D. Figueiredo, R. Santos, D. Santos, L. Barroso, G. Alves, J. Vieira, L. Guimarães, C. Santos , L. Maciel |
38. Delineation of 'Management Classes' Within Non-Irrigated Maize Fields Using Readily Available Reflectance Data and Their Correspondence to Spatial Yield VariationMaize is grown predominantly for silage or gain in North Island, New Zealand. Precision agriculture allows management of spatially variable paddocks by variably applying crop inputs tailored to distinctive potential-yield limiting areas of the paddock, known as management zones. However, uptake of precision agriculture among in New Zealand maize growers is slow and limited, largely due to lack of data, technical expertise and evidence of financial benefits. Reflectance data of satellite and areal... D.C. Ekanayake, J. Owens, A. Werner, A. Holmes |
39. ADAPT: A Rosetta Stone for Agricultural DataModern farming requires increasing amounts of data exchange among hardware and software systems. Precision agriculture technologies were meant to enable growers to have information at their fingertips to keep accurate farm records (and calculate production costs), improve decision-making and promote efficiencies in crop management, enable greater traceability, and so forth. The attainment of these goals has been limited by the plethora of proprietary, incompatible data formats among... D.D. Danford, K.J. Nelson, S.T. Rhea, M.W. Stelford, R. Ferreyra, J.A. Wilson, B.E. Craker |
40. Main Stream Precision Farming - 7.000 VRA Maps for Winter RapeseedSEGES is owned by the Danish farmers and is an agricultural advisory centre advising landowners with a total of 2.1 mill hectare. One of SEGES’s goals is to make precision farming mainstream. One step in the process of making precision farming mainstream was in 2016 to give all farmers access to the free internet application CropSAT.dk. Here farmers can make variable rate application (VRA) maps based on satellite data from Sentinel-2. But this is not enough to make... R. Hoerfarter |
41. Precision Fall Urea Fertilizer Applications: Timing Impact on Carbon Dioxide, Ammonia Volatilization and Nitrous Oxide EmissionsTo minimize ammonia (NH3) volatilization and nitrous oxide (N2O) emissions from fall applied fertilizer, it is generally recommended to not apply the fertilizer until the soil temperature decreases below 10 C. However, this recommendation is not based on detailed measurements of NH3and N2O emissions. The objective of this study was to determine the influence of fertilizer application timing on nitrous oxide, carbon dioxide, and ammonia volatilization emissions. Nitrogen fertilizer was... S. Thies, D.E. Clay, S. Bruggeman, D. Joshi, S. Clay, J. Miller |
42. Estimating Litchi Canopy Nitrogen Content Using Simulated Multispectral Remote Sensing DataThis study aims at evaluating the performance of seven highly spatial resolution remote sensing data in litchi canopy nitrogen content estimation. The litchi canopy reflectance were collected by ASD field spectrometer. Then the canopy spectral data were resampled based on the spectral response functions of each satellite sensors (Geo-eye, GF-WFV1, Rapid-eye, WV-2, Landsat 8, WV-3, and Sentinel-2). The spectral indices in literature were derived based on the simulated data. Meanwhile, the successive... D. Li, H. Jiang, S. Chen, C. Wang |
43. Map Whiteboard As Collaboration Tool for Smart Farming Advisory ServicesPrecision agriculture, a branch of smart farming, holds great promise for modernization of European agriculture both in terms of environmental sustainability and economic outlook. The vast data archives made available through Copernicus and related infrastructures, combined with a low entry threshold into the domain of AI-technologies has made it possible, if not outright easy, to make meaningful predictions that divides individual agricultural fields into zones where variable rates... K. Charvat, R. Berzins, R. Bergheim, F. Zadrazil, J. Macura, D. Langovskis, H. Snevajs, H. Kubickova, S. Horakova, K. Charvat jr. |
44. Using On-the-Go Soil Sensors to Assess Spatial Variability within the KS Wheat Breeding ProgramIn plant breeding the impacts of genotype by environment interactions and the challenges to quantify these interactions has long been recognized. Both macro and microenvironment variations in precipitation, temperature and soil nutrient availability have been shown to impact breeder selections. Traditionally, breeders mitigate these interactions by evaluating genotype performance across varying environments over multiple years. However, limitations in labor, equipment and seed availably can limit... B. Evers, M. Rekhi, G. Hettiarachchi, S. Welch, A. Fritz, P.D. Alderman, J. Poland |
45. Is Row-unit Vibration Affected by Planter Speeds and Downforce?Row-unit vibration is an issue created mainly by planter`s opening disks and gauge-wheels contact with the ground. Variability on row-unit vibration could interfere on seed metering and delivery process, affecting crop emergence and final stand. With the amount of embedded technology present on planters, producers are being encouraged to increase planting speeds, which is also one of the main factors for row-unit vibration increasement. In this way, knowing the proper speeds, and using other instruments... L.P. Oliveira, B.V. Ortiz, G.T. Morata, T. Squires, J. Jones |
46. Agriculture Machine Guidance Systems: Performance Analysis of Professional GNSS ReceiversGNSS (Global Navigation Satellite Systems) plays nowadays a major role in different civilian activities and is a key technology enabling innovation in different market sectors. For instance, GNSS-enabled solutions are widespread within the Precision Agriculture and, among them, applications in the field of machinery guidance are commonly employed to optimize typical agriculture practices. The scope of this paper is to present the outcomes of the agriculture testing campaign performed,... J. Capolicchio, D. Mennuti, I. Milani, M. Fortunato, R. Petix, J. Reyes gonzalez, M. Sunkevic |
47. The ISO Strategic Advisory Group for Smart Farming: a Multi-pronged Opportunity for Greater Global InteroperabilityAgriculture is becoming increasingly complex and producers must secure their profitability, sustainability, and freedom to operate under a progressively more challenging set of constraints such as climate change, regulatory pressure, changes in consumer preferences, increasing cost of inputs, and commodity price volatility. We have not, however, yet reached the level of data interoperability required for a truly "smart" farming that can tackle the aforementioned problems... R. Ferreyra, J. Lehmann |
48. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV ImageryPollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness of... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack |
49. Interoperability As an Enabler for Principled Decision-making in Irrigation: the Precision Agriculture Irrigation Language (PAIL)Fresh water is a scarce resource, and agriculture consumes a high fraction of it worldwide. As climate change increases the likelihood of high temperatures and droughts, irrigation becomes an increasingly attractive option for managing crop production risks. Unfortunately, and despite decades of efforts by professional associations to promote the use of a principled, data-driven approach to irrigation scheduling often called scientific irrigation scheduling (SIS), the fraction of farmers... R. Ferreyra, C.C. Hillyer, H.D. Fuller, B. Craker, K. Watanabe |
50. Standards for Data-driven Agrifood Systems, One Year After the ISO Strategic Advisory Group for Smart FarmingThe lack of data interoperability is a major obstacle for the data-driven, principled multi-objective decision-making required for modern agrifood systems to help meet the UN Sustainable Development Goals. Aware of this, the International Organization for Standardization (ISO) chartered a Strategic Advisory Group for Smart Farming (SAG-SF) to survey the existing standardization landscape of the domain within ISO, to identify gaps where additional standardization is needed, and to provide a strategic... R. Ferreyra, J. Lehmann, J.A. Wilson |
51. Assessing Soybean Water Stress Patterns and ENSO Occurrence in Southern Brazil: an in Silico ApproachWater stress (WS) is one of the most important abiotic stresses worldwide, responsible for crop yield penalties and impacting food supply. The frequency and intensity of weather stresses are relevant to delimitating agricultural regions. In addition, El Nino Southern Oscillation (ENSO) has been employed to forecast the occurrence of seasonal WS. Lastly, planting date and cultivar maturity selection are key management strategies for boosting soybean (Glycine max (L.) Merr.) yield... A. Carcedo, L.F. Antunes de almeida, T. Horbe, G. Corassa, L.P. Pott, I. Ciampitti, G.D. Hintz, T. Hefley, R.A. Schwalbert, V. Prasad |
52. 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 |
53. An Open Database of Crop Yield Response to Fertilizer Application for SenegalFood security is one of the major global challenges today. Africa is one of the continents with the largest gaps in terms of challenges for food security. In Senegal, about 60% of the population resides in rural areas and the cropping systems are characterized as a low productivity system, low input and in reduced areas, smallholder subsistence systems. Increasing crop productivity would have a positive impact on food security in this country. One of the main factors limiting crop productivity... F. Gomez, A. Carcedo, A. Diatta, L. Nagarajan, V. Prasad, Z. Stewart, S. Zingore, I. Ciampitti, P. Djighaly |
54. 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 of... A. Tasissa, L. Li, J.M. Murphy |
55. Evaluating the Potential of In-season Spatial Prediction of Corn Yield and Responses to Nitrogen by Combining Crop Growth Modeling, Satellite Remote Sensing and Machine LearningNitrogen (N) is a critical yield-limiting factor for corn (Zea mays L.). However, over-application of N fertilizers is a common problem in the US Midwest, leading to many environmental problems. It is crucial to develop efficient precision N management (PNM) strategies to improve corn N management. Different PNM strategies have been developed using proximal and remote sensing, crop growth modeling and machine learning. These strategies have both advantages and disadvantages. There is... X. Zhen, Y. Miao, K. Mizuta, S. Folle, J. Lu, R.P. Negrini, G. Feng, Y. Huang |
56. Can Soil Fertility Data and Topography Predict Yield Stability Zones for Corn Fields in New York?Yield monitor systems play a vital role in precision agriculture given their ability to capture and map within-field yield variability. When three or more years of yield data are available, yield stability zone maps can be generated to show both the spatial and temporal variability of yield within a field. Based on the farm’s overall temporal mean and standard deviation for a specific crop, we can classify areas in the field as consistently high- (Q1) or low-yielding (Q4), and variably high-... M. Marcaida, X. Zhang, S. Srinivasagan, S. Shajahan, Q. Ketterings |
57. Single-strip Spatial Evaluation Approach: a Simplified Method for Enhanced Sustainable Farm ManagementOn-farm experimentation (OFE) plays a pivotal role in evaluating and validating the effectiveness of agricultural practices and products. The results of OFE enable farmers to act and make changes that can enhance the farm’s economic and environmental sustainability. Experimental designs can be a barrier to the adoption of OFE. The conventional approach often involves randomized complete block designs with 3 to 5 replications in the field, which can be space-intensive and disrupt workflow... S. Srinivasagan, Q. Ketterings, M. Marcaida, S. Shajahan, J. Ramos-tanchez, J. Cho, , L. Thompson, J. Guinness, R. Goel |
58. Quantifying Boom Movement in Agricultural Sprayer Booms Using Neural Networks for Real-world Field ScenariosApplication rate errors in self-propelled agricultural sprayers remain a significant concern, necessitating a comprehensive understanding of boom movement during actual field operating scenarios. This study introduces new objectives to quantify boom movement across commercial sprayers when operated by different individuals and compares these movements among various machines. The goal is to develop a metric that identifies potential improvement needs for boom height control system. The approach... T. Kaloya, A. Sharda, A. Dalal |
59. Simultaneously Estimating Crop Biomass and Nutrient Parameters Using UAS Remote Sensing and Multitask LearningRapid and accurate estimation of crop growth status and nutrient levels such as aboveground biomass, nitrogen, phosphorus, and potassium concentrations and uptake is critical with respect to precision agriculture and field-based crop monitoring. Recent developments in Uncrewed Aircraft Systems (UAS) and sensor technologies have enabled the collection of high spatial, spectral, and temporal remote sensing data over large areas at a lower cost. Coupled deep learning-based modeling approaches with... P. Kovacs, M. Maimaitijiang, B. Millett, L. Dorissant, I. Acharya, U.U. Janjua, K. Dilmurat |
60. Decision Making Factors of Precision Agricultural Practices in South DakotaA survey among South Dakota Farmers was conducted to document current nutrient management practices. The survey included questions regarding adoption and use of precision ag technologies in addition to information considered to create prescription maps for variable fertilizer and seeding rates. The survey collected demographic information from the producers. The presentation will also highlight how farm size, farm location, farmer/decision maker’s age and/or education level influences... P. Kovacs, J. Clark, J. Schad, E. Avemegah |
61. Utilizing Thermal and RGB Imaging for Nutrient Deficiency and Chlorophyll Status Evaluation in PlantsAs global population growth and climate change continue to challenge food security, addressing agricultural issues efficiently and cost-effectively is vital for enhancing productivity. Integrating technology into agriculture, particularly through timely interventions, offers promising solutions to mitigate challenges before they escalate. This study investigates the feasibility of using thermal and RGB imaging as efficient, non-destructive methods to assess nutrient deficiencies and chlorophyll... A.H. Rabia, D.G. Allam, E.F. Abdelaty, E.A. Abderaouf |
62. 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 |
63. 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 spectral... L. Thomas, B. Jakimow, A. Janz, P. Hostert, A. Lajunen |