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1. Application of Information Technologies in Precision ApicultureApiculture, widely known as beekeeping, is one of the agriculture’s sub directions, where Precision Agriculture (PA) methods can be successfully applied. Adaptation of PA methods and technics into Apiculture, as well as integrating information technologies into beekeeping process can change and improve the beekeepers understanding of bee... E. Stalidzans, A. Zacepins, J. Meitalovs |
2. Evaluation of Photovoltaic Modules at Different Installation Angles and Times of the DaySeveral electricity-consuming components for cooling and heating, illumination, ventilation, and irrigation are used to maintain proper environments of protected crop cultivation facilities. Photovoltaic system is considered as one of the most promising alternative power source for protected cultivation. Effects of environm... S. Chung, J. Kong, Y. Huh, K. Bae, S. Hur, D. Lee, Y. Chae |
3. Climatological Diagnostic Analysis: A Case Study for Parbhani District in Marathwada Region of India... S.N. Pawar, A.K. Gore, G.U. Shinde, M.S. Pendke |
4. Toward More Precise Sugar Beet Management Based On Geostatistical Analysis Of Spatial Variabilty Within FieldsAbstract: Sugar beet (Beta vulgaris L.) yields in England are predicted to increase in the future, due to the advances in plant breeding and agronomic progress, but the intra-field variations in yield due to the variability in soil properties is considerable. This paper explores the within-field spatial variation in environmental variables and crop development during the growing season and their link to spatial variation in sugar beet y... A.J. Murdoch, S.A. Mahmood |
5. Estimating Spatial Variation In Annual Pasture YieldYield mapping is an essential tool for precision management of arable crops. Crop yields can be measured once, at harvest, automatically by the harvesting machinery, and be used to inform a wide range of activities. However yield mapping has had minimal adoption by pastoral farmers. Yield mapping is also a potentially valuable tool for precision management of pastures. However it is difficult to practically map yields on pastures, as they... S.J. Dennis, W. Clarke-hill, A. Taylor, R. Dynes, K. O'neill, T. Jowett |
6. The Spatial And Temporal Variability Analysis Of Wheat Yield in suburban of BeijingAbstract: The yield map is the basis of the fertilization maps and plant maps. In order to diagnose the cause of variation accurately, not only the spatial variation of annual yield data, but also the successive annual yield data of temporal variability should be understood.The introduction of yield monitor system, global positioning system (GPS), and geographic information system have provided new methods to obtain wheat yield in precision agriculture.... Z. Meng, Z. Wang, G. Wu, W. Fu, X. An |
7. First Results Of Development Of A Smart Farm In The NetherlandsGNSS technology has been introduced on about 20 % of the Dutch arable farms in The Netherlands today. Use of sensor technology is also slowly but gradually being adopted by farmers, providing them large amounts of digital data on soil, crop and climate conditions. Typical data are spatial variation in soil organic matter, crop biomass, crop yield, and presence of pests and diseases. We still have to make major steps to use all this data in a way that agriculture becomes more sus... T. Feher, C. Kocks, C. Kempenaar, K. Westerdijk |
8. A Comprehensive Model for Farmland Quality Evaluation with Multi-source Spatial InformationFarmland quality represents various properties, including two parts of natural influencing factors and social influencing factors. The natural factors and social factors are interrelated and interaction, which determine the developing direction of farmland system. In order to overcome the limitation of subjective factors and fuzzy incompatible information, a more scientific evaluation method of farmland quality should be developed to reflect the essential characteristic of farml... Y. Dong, Y. Wang, X. Song, X. Gu |
9. Physiological Repsonses Of Corn To Variable Seeding Rates In Landscape-Scale Strip TrialsMany producers now have the capability to vary seeding rates on-the-go. Methods are needed to develop variable rate seeding approaches in corn but require an understanding of the physiological response of corn to soil-landscape and weather conditions. Interplant competition fundamentally differs at varied seeding rate and may affect corn leaf area, transpiration, plant morphology, and assimilate partitioning. Optimizing these physiological effects with optimal seeding rates in a site-spe... D.B. Myers, N.R. Kitchen, K.A. Sudduth, B.J. Leonard |
10. Spatial Variation And Correlation Between Electric Conductivity (EM38), Penetration Resistance And CO2 Emissions From A Cultivated Peat SoilPeatlands in their natural state accumulate organic matter and bind large quantities of carbon (5 - 50 g C/m2/year). The drainage and cultivation of peat soils increase the aeration of the soil, which increase the brake down of the organic matter. The degradation of the organic material release greenhouse gases such as CO2, N2O and CH4. CO2 emissions dominate when the soil has high oxygen levels, while CH4 mainly ... &.E. Berglund |
11. Penetration Resistance And Yield Variation At Field ScaleIn order to better explain spatial variations within fields, soil physical properties need to be studied in more depth. Relationships between soil physical parameters and yield, especially in the subsoil, are seldom studied since the characterization of soil variability at field or subfield scale using conventional methods is a labor intensive, very expensive, and time-consuming procedure, particularly when high-resolution data is required. However, soil physical prope... E. Bölenius, J. Arvidsson |
12. Optimization Of Maize Yield: Relationship Between Management Zones, Hybrids And Plant PopulationCorn is highly sensitive to variations in plant population and it is one of the most important practices influencing in grain yield. Knowledge about plant physiology and morphology allow understanding how the crop interacts with plant population variation. Considering that for each production system there is a population that optimizes the use of available resources it is necessary to manage plant population to reach maximum grain yield on each particular environment. This study... A.A. Anselmi, J.P. Molin, R. Khosla |
13. Water And Nitrogen Use Efficiency Of Corn And Switchgrass On Claypan Soil LandscapesClaypan soils cover a significant portion of Missouri and Illinois crop land, approximately 4 million ha. Claypan soils, characterized with a pronounced argilic horizon at or below the soil surface, can restrict nutrient availability and uptake, plant water storage, and water infiltration. These soil characteristics affect plant growth, with increasing depth of the topsoil above the claypan horizon having a strong positive correlation to grain crop production. In the case of low... A. Thompson, D.L. Boardman, N. Kitchen, E. Allphin |
14. Heavy Metal PB2+ Pollution Detection In Soil Using Terahertz Time-domain Spectroscopy For Precision AgricultureSoil is an important natural resource for human beings. With the rapid development of modern industry, heavy metals pollution in soil has made prominent influences on farmland environment. It was reported that, one fifth of China's cultivated lands and more than 217,000 farms in the US have been polluted at different levels by heavy metals. The crop grows in the polluted soil and the heavy metal ions transfer from soil to the plant and agro-products. As a result, the crop yi... C. Zhao, B. Li |
15. Soil And Crop Spatial Variability In Cotton Grown On Deep Black Cotton SoilsSoil spatial variation is observed under similar management situation in cotton growing soils of Northern Karnataka. In view of this an experiment was conducted to study the spatial variability in soil with respect soil reaction (pH), Electrical conductivity (Ec), Organic carbon (OC%), all major (N,P,K), secondary (Ca, Mg and S) and micronutrients (Fe, Zn, Cu and Mn) by assessing soil nutrients in deep black cotton soils of the experimental station ... C.C. Parashuramegowda |
16. 3D Map in the Depth Direction of Field for Precision AgricultureBy a change in eating habits with economic development and the global population growth, we have been faced with the need for increased food production again. In order to solve the food problem in the future, the introduction of agriculture organization is progressing in emerging countries as well as developed countries. However, the occurrence of natural disasters and abnormal weather, which is becoming a worldwide problem at present, is further weakening the crops of far... H. Umeda, S. Shibusawa, Q. Li, K. Usui, M. Kodaira |
17. Developing A High-Resolution Land Data Assimilation And Forecast System For Agricultural Decision SupportTechnological advances in weather and climate forecasting and land surface and hydrology modeling have led to an increased ability to predict soil temperature, and soil moisture, near-surface weather elements. These variables are critical building blocks to the development of high-level agriculture-specific models such as pest models and crop yield models. The National Center for Atmospheric Research (NCAR) has developed a high-resolution agriculture-oriented land-data assimilat... W. Mahoney, M. Barlage, D. Gochis, F. Chen |
18. Assessing Definition Of Management Zones Trough Yield MapsYield mapping is one of the core tools of precision agriculture, showing the result of combined growing factors. In a series of yield maps collected along seasons it is possible to observe not only the spatial distribution of the productivity but also its spatial consistency among different seasons. This work proposes the study of distinct methods to analyze yield stability in grain crops regarding its potential for defining management zones from a historical sequence of yield maps. Two ... M.T. Eitelwein, J.P. Molin, M. Spekken, R.G. Trevisan |
19. Spatial Dependence Of Soil Compaction In Annual Cycle Of Different Culture Of Cane Sugar For Sandy SoilThe Currently practiced mechanization for the production of sugar cane involves a heavy traffic of machinery and equipment. Studying the culture in its development environment generates a huge amount of information to fit the top managements and varieties for specific environments. The sugar cane cultivation has a heavy traffic of machinery and equipment, having more than 20 operations per cycle, and being more intense during harvest, providing incre... I. Marasca, F.C. Masiero, D.A. Fiorese, S.S. Guerra, K.P. Lancas |
20. A Method To Estimate Irrigation Efficiency With Evapotranspiration DataIrrigation efficiency is defined as the ratio of irrigation water consumed by the crops to the water diverted (Wg) from a river or reservoir or wells. This terminology serves for better irrigation systems designation and irrigation management practices improvement. But it is hard or high cost with labor intensity to estimate irrigation efficiency from field measurement. This paper proposes an estimating method of irrigation efficiency at the scale of irrigat... H. Zeng, B. Wu, N. Yan |
21. Precision Agriculture In Sugarcane Production. A Key Tool To Understand Its Variability.Precision agriculture (PA) for sugarcane represents an important tool to manage local application of fertilizers, mainly because sugarcane is third in fertilizer consumption among Brazilian crops, after soybean and corn. Among the limiting factors detected for PA adoption in the sugarcane industry, one could mention the cropping system complexity, data handling costs, and lack of appropriate decision support systems. The objective of our research group ha... P.S. Graziano magalhães, G.M. Sanches, O.T. Kolln, H.C. Franco, O.A. Braunbeck, C. Driemeier |
22. Exploiting The Variability In Pasture Production On New Zealand Hill Country.New Zealand has about four million hectares in medium to steep hill country pasture to which granular solid fertiliser is applied by airplane. On most New Zealand hill country properties where cultivation is not possible the only means of influencing pasture production yield is through the addition of fertilizers and paddock subdivision to control grazing and pasture growth rates. Pasture response to fertilizer varies in production zones within the farm which can be modell... M.Q. Grafton, P.J. Mcveagh, R.R. Pullanagari, I.J. Yule |
23. Study Of Spatio-Temporal Variation Of Soil Nutrients In Paddy Rice Planting FarmIt is significant to analysis the spatial and temporal variation of soil nutrients for precision agriculture especially in large-scale farms. For the data size of soil nutrients grows once after sampling which mostly by the frequency of one year or months, to discover the changing trends of exact nutrient would be instructive for the fertilization in the future. In this study, theories of GIS and geostatistics were used to characterize the spatial and temporal variability of soi... C. Wang, T. Chen, J. Dong, C. Li |
24. Site-Specific Variability Of Grape Composition And Wine QualityPrecision Viticulture (PV) is the application of site-specific tools to delineate management zones in vineyards for either targeting inputs or harvesting blocks according to grape maturity status. For the creation of management zones, soil properties, topography, canopy characteristics and grape yield are commonly measured during the growing season. The majority of PV studies in winegrapes have focused on the relation of soil and vine-related spatial data with grape co... S. Fountas, Y. Kotseridis, A. Balafoutis, E. Anastasiou, S. Koundouras, S. Kallithraka, M. Kyraleou |
25. Probability Distributions And Alternative Transformations Of Soil Test NO3-N And PO4-P, Implications For Precision AgricultureRecommendations for fertilizer N in crop production and precision agriculture depend on statistical analyses of data which represent soil NO3-N and PO4-P fertility typical of management zones and fields. Non-normal distributions of soil test N are commonly log transformed prior to statistical analysis for interpolation with methods such as kriging, regression, or principle component analysis. These data are transformed to ensure that analysis meet the assumptions of normality... A. Moulin |
26. Does Nitrogen Balance Surplus Done At Field Level Help To Assess Environmental Effects Of Variable Nitrogen Application In Winter Wheat?Increased nitrogen use efficiency (NUE) is important as a specific consideration to decrease negative impacts of nitrogen (N) on the environment and provide better crop quality. Therefore, in many European countries N is used with restrictions due to UE regulations, set to increase NUE. This is particularly important in wheat production because this crop in EU accounts for 48% of cereal production and uses about 25% of total N-fertilizer applied. One of the methods applied to increase NU... S.M. Samborski |
27. Assessing the Distribution Uniformity of Broadcast-interseeded Cover Crops at Different Crop Stages by an Unmanned Aerial VehicleDrones can now carry larger payloads and have become more affordable, making them a viable option to use for broadcast-interseeding cover crops in the fall, prior to main crop harvest. This strategy has become popular in Ohio over the past two years. However, this new strategy arose quickly with a limited understanding of field performance of the drone’s distribution uniformity under different parameters such as rates, swath widths, speeds, or cash crop type. Therefore, the objective of... A.D. Thomas, J.P. Fulton, S. Khanal, O. Ortez, G. Mcglinch |
28. Transforming Precision Agriculture Education, Research and Outreach in Sub-saharan Africa Through Intra-africa CooperationProductivity and profitability of sub-Saharan (SSA) agriculture can be enhanced greatly through the adoption of precision agriculture technologies and tools. However, until 2020 when the African Plant Nutrition Institute (APNI) established the African Association for Precision Agriculture (AAPA), most SSA PA enthusiast worked in isolation. The AAPA was formed to innovate Africa’s agricultural industry by connecting PA science to its practice and disseminate PA tailored to the need... K.A. Frimpong, S. Phillips, V. Aduramigba-modupe, N. Fassinou hotegni, M. Mechri, M. Mishamo, J.M. Sogbedji, Z. hazzoumi, R. Chikowo, M. Fodjo kamdem |
29. A Case for Increased Precision Pesticide Application Adoption in California Perennial Specialty Crop ProductionMaintaining high and quality crop yields in California’s diverse agriculture requires both good crop care through nutrient management and water management and effective crop protection through integrated pest management (IPM). Despite the promotion and adoption of non-chemical IPM practices in California such as sanitation and biological control, pesticide use remains inevitable in many cases. According to the 2021 California Pesticide Use Report, 37,444,331 kg of pesticide was used in ... P.A. Larbi |
30. Pesticide Application Management Toolset for Improved Worker ProtectionThe practice of pesticide use has been widely adopted by production agriculture to maximize yields since the 1950s. Even though it provides beneficial economic returns to the farmers, it also enhances the risk of environmental pollution and is directly associated with the risk of poisoning to agricultural workers. While adhering to United States Federal Environmental Protection Agency (EPA) Worker Protection Standard (WPS) guidelines, the current systems need considerable time to provide cruc... C. Narayana, N. Thorson, J.D. Luck |
31. Participatory Irrigation Extension Programs to Increasing Adoption of Best Irrigation StrategiesFarmers in Alabama, Tennessee, and other US southeastern states lack experience in irrigation water management and adoption of the state-of-the-art technologies and practices to increase irrigation water use efficiency. Several federal and state-funded projects are being implemented to demonstrate and train farmers and consultants on irrigation scheduling strategies and variable rate irritation. Half a dozen on-farm demonstration sites are selected every year to evaluate, demonstrate, and tra... L. Nunes, E. Francisco, R. Prasad, B.V. Ortiz, E. Abban-baidoo , M. Worosz, M. Robinette , C. O'connor, A. Gamble |
32. Automated In-field Ornamental Nursery Plant Counting and Quality Assessment with End-to-end Deep Learning for Inventory ManagementEfficient inventory management and rigorous quality evaluation play crucial roles for monitoring sales, yield, space utilization, production schedules, and quality enhancements in the ornamental nursery sector. The current method for conducting inventory and quality assessments is through manual plant counting, even when dealing with thousands of plants. The prevailing approach is inefficient, time consuming, labor intensive, potential inaccuracies, and high expenses. Given the continuous dec... H.H. Syed, T. Rehman |
33. AI-based Pollinator Using CoreXY RobotThe declining populations of natural pollinators pose a significant ecological challenge, often attributed to the adverse effects of pesticides and intensive farming practices. To address the critical issue of pollination in the face of diminishing natural pollinators, we are pioneering an AI-based pollinator that utilizes a CoreXY pollination system. This solution aims to augment pollination efforts in agriculture, increasing yields and crop quality while mitigating the adverse impacts of pe... H. Kulhandjian, M. Kulhandjian, D. Rocha, B. Bennett |
34. AI-based Fruit Harvesting Using a Robotic ArmFruit harvesting stands as a pivotal and delicate process within the agricultural industry, demanding precision and efficiency to ensure both crop quality and overall productivity. Historically reliant on manual labor, this labor-intensive endeavor has taken a significant leap forward with the advent of autonomous jointed robots and Artificial Intelligence (AI). Our project aims to usher in a new era in fruit harvesting, leveraging advanced technology to perform this essential task autonomous... H. Kulhandjian, N. Amely, M. Kulhandjian |
35. Creating a Comprehensive Software Framework for Sensor-driven Precision AgricultureRobots and GPS-guided tractors are the backbone of smart farming and precision agriculture. Many companies and vendors contribute to the market, each offering their own customized solutions for common tasks. These developments are often based on vendor-specific, proprietary components, protocols and software. Many small companies that produce sensors, actuators or software for niche applications could contribute their expertise to the global efforts of creating smart farming solutions, if the... O. Scholz, F. Uhrmann, M. Weule, T. Meyer, A. Gilson, J. Makarov, J. Hansen, T. Henties |
36. Enhancing Precision Agriculture Through Dual Weed Mapping: Delineating Inter and Intra-row Weed Populations for Optimized Crop ProtectionIn the field of precision agriculture, effective management of weed populations is essential for optimizing crop yield and health. This paper presents an innovative approach to weed management by employing dual weed mapping techniques that differentiate between inter-row and intra-row weed populations. Utilizing advanced imaging and data analysis of CropEye images collected by the Robotti robot from AgroIntelli (AgroIntelli A/S, Aarhus, Denmark), we have developed methods to generate distinct... R.N. Jørgensen, S. Skovsen, O. Green, C.G. Sørensen |
37. Voronoi-based Ant Colony Optimization Approach: Autonomous Robotic Swarm Navigation for Crop Disease DetectionThe early detection of agricultural diseases is essential for sustaining food production and economic viability over the long term. To improve disease detection in agriculture, this paper presents an innovative computational approach that utilizes the Voronoi-based Ant Colony Optimization (V-ACO) algorithm with Swarm Robotics (SR). Inspired by the social behaviors observed in insect colonies such as honeybees and ants, SR offers new opportunities for precision farming. SR utilizes the coordin... S. Gummi, M. Alahe, Y. Chang, C. Pack |
38. Partial Fruitlet Cutting Approach for Robotic Apple ThinningEarly season thinning of apple fruitlets is a crucial task in commercial apple farming, traditionally accomplished through chemical sprays or labor-intensive manual operations. These methods, however, are faced with the challenges of diminishing labor availability as well as environmental and/or economic sustainability. This research examines 'partial fruitlet cutting,' a novel nature-assisted strategy, as an alternative method for automated apple thinning in orchards. The study hypot... R. Sapkota, M. Karkee |
39. Real Time Application of Neural Networks and Hardware Accelerated Image Processing Pipeline for Precise Autonomous Agricultural SystemsModern agriculture is increasingly turning to automation and precision technology to optimize crop management. In this context, our research addresses the development of an autonomous pesticide spraying rover equipped with advanced technology for precision agriculture. The primary goal is to use a neural network for real-time aphid detection in Sorghum crops, enabling targeted pesticide application only to infested plants. To accomplish this, we've integrated cutting-edge technologies and... J. Raitz persch, R. Harsha chepally, N.K. Piya |
40. Advancements in Agrivoltaics: Autonomous Robotic Mowing for Enhanced Management in Solar FarmsAgrivoltaics – the co-location of solar energy installations and agriculture beneath or between rows of photovoltaic panels – has gained prominence as a sustainable and efficient approach to land use. The US has over 2.8 GW in Agrivoltaics, integrating crop cultivation with solar energy. However, effective vegetation management is critical for solar panel efficiency. Flat, sunny agricultural land accommodates solar panels and crops efficiently. The challenge lies in managing grass... S. Behera, S. Pitla |
41. Implementation of Autonomous Material Re-filling Using Customized UAV for Autonomous Planting OperationsThis project introduces a groundbreaking use case for customized Unmanned Aerial Vehicles (UAVs) in precision agriculture, focused on achieving holistic autonomy in agricultural operations through multi-robot collaboration. Currently, commercially available drones for agriculture are restrictive in achieving collaborative autonomy with the growing number of unmanned ground robots, limiting their use to narrow and specific tasks. The advanced payload capacities of multi-rotor UAVs,... V. Muvva, H. Mwunguzi, S. Pitla, K. Joseph |
42. Advancements in Agricultural Robots for Specialty Crops: a Comprehensive Review of Innovations, Challenges, and ProspectsThe emergence of robot technology presents a timely opportunity to revolutionize specialty crop production, offering crucial support across various activities such as planting, supporting general traits, and harvesting. These robots play a pivotal role in keeping stakeholders up-to-date of developments in their production fields, while providing them the capability to automate laborious tasks. Then, to elucidate the advancements in this domain, we present the results of a comprehensive review... M. Barbosa, R. Santos, L. Sales, L. Oliveira |
43. Utilizing ArUco Markers to Define Implement BoundariesJohn Deere and Blue River Technology’s autonomous tillage system combines multidisciplinary efforts and cutting-edge technology to achieve Level 5—Unsupervised Autonomy. To create this engineering marvel, countless parameters need defined to ensure safe operation of the system; some of these parameters are static, while other of these parameters are dynamic. One particular set of parameters define the tillage implement’s boundaries for the software stack to utilize, and toda... R. Sleichter |
44. Automated Detection and Length Estimation of Green Asparagus Towards Selective HarvestingGreen asparagus is an important vegetable crop in the United States (U.S.). Harvesting the crop is notoriously labor-intensive, accounting for over 50% of production costs. There is an urgent need to develop harvesting automation technology for the U.S. asparagus industry to remain sustainable and competitive. Despite previous research and developments on mechanical asparagus harvesting, no practically viable products are available because of their low harvest selectivity and significant yiel... J. Xu, Y. Lu |
45. Agrosense: AI-enabled Sensing for Precision Management of Tree CropsMonitoring the tree inventory and canopy density and height frequently is critical for researchers and farm managers. However, it is very expensive and challenging to manually complete these tasks weekly. Therefore, a low-cost and artificial intelligence (AI) enhanced sensing system, Agrosense, was developed for tree inventory, canopy height measurement, and tree canopy density classification in this study. The sensing system mainly consisted of four RGB-D cameras, two Jetson Xavier NX, and o... C. Zhou, Y. Ampatzidis, H. Guan, W. Liu, A. De oliveira costa neto, S. Kunwar, O. Batuman |
46. SurePoint Ag Systems - Sponsor Presentation... B. Downing |
47. Prediction of Field-scale Evapotranspiration Using Process Based Modeling and Geostatistical Time-series InterpolationIrrigation scheduling depends on the combination of evaporative demand from the atmosphere, spatial and temporal heterogeneity in soil properties and changes in crop canopy during a growing season. This on-farm trial is based on data collected in 72-acre processing tomato field in Central Valley of California. The Multiband Spectrometric Arable Mark 2 sensors at three different locations in the field. Multispectral and thermal imagery provided by Ceres Imaging were collected eight times durin... G. Jha, F. Nazrul, M. Nocco, M. Pagé fortin, B. Whitaker, D. Diaz, A. Gal, R. Schmidt |
48. 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.) y... 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 |
49. 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 |
50. Spatio-temporal Variability of Intra-field Productivity Using Remote SensingUnderstanding the spatiotemporal variability in intra-farm productivity is crucial for management in making agronomic decisions. Furthermore, these decision-making processes can be enhanced using spatial data science and remote sensing. This study aims to develop a framework to asses the spatio-temporal variability of intra-farm productivity through historical satellite data and climate data. Historical satellite data and rainfall information from diverse fields across the United States (2016... E. Van versendaal, C. Hernandez, P. Kyveryga, I. Ciampitti |
51. Machine Learning Algorithms in Detecting Long-term Effect of Climatic Factors for Alfalfa Production in KansasThe water levels of the Ogallala Aquifer are depleting so much that agricultural land returns in Kansas are expected to drop by $34.1 million by 2050. It is imperative to understand how frequent droughts and the contrasting rates of groundwater withdrawal and recharge are affected by climate shifts in Kansas. Alfalfa, the ‘Queen of Forages’, is a water demanding crop which supplies high nutritional feed for beef industry that offered Kansas producers a $500 million production valu... F. Nazrul, J. Kim, S. Dey, S. Palla, D. Sihi, B. Whitaker, G. Jha |
52. Dimensionality Reduction and Similarity Metrics for Predicting Crop Yields in Sparse Data MicroclimatesThis study explores and develops new methodologies for predicting agricultural outcomes, such as crop yields, in microclimates characterized by sparse meteorological data. Specifically, it focuses on reducing the dimensionality in time series data as a preprocessing step to generate simpler and more explainable forecast models. Dimensionality reduction helps in managing large data sets by simplifying the information into more manageable forms without significant loss of information. We explor... L. Huender, M. Everett |
53. Using Simulation Modeling to Evaluate the Corn Response to Deficit Irrigation Imposed During Reproductive PeriodIn Alabama, as in many regions of the southeastern states, flash droughts and rising temperatures present significant challenges to the sustainability of agricultural systems. Specifically maize, a crop with a high water demand, faces production risks due to these adverse conditions. The study explores the optimum irrigation scheduling strategies on maize (Zea mays L.) in the reproductive growth stages through the evaluation of the impact of three irrigation treatments, defined by Maximum All... J.S. Velasco, B.V. Ortiz, L. Nunes, R. Prasad, G. Hoogenboom |