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1. 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 ... E. Borghi, A. Luchiari junior, L. Bortolon, E.S. Bortolon, R.Y. Inamasu, A.C. Bernardi, J.C. Avanzi |
2. Strategies For Scientific Communication Of Precision Agriculture In BrazilScientific knowledge popularization is the way to the society access technical scientific advances. The challenge is to increase the means, channels and processes of information and relationship with society and decode scientific issues into a format that makes knowledge accessible. The Embrapa Precision Agriculture Network has been used scientific communication strategies at the traditional and new media, as a way of approach with various stakeholders, contributing to the const... C.V. fragalle, J.C. Silva, E.P. fragalle, R.Y. Inamasu, A.C. Bernardi |
3. Precision Agriculture Use In Selected Agricultural Regions In BrazilInvestment in technology brought Brazil to the position among the top agricultural producers in the world. Brazilian agricultural production has increased drastically as a result of productivity growth instead expansion in area. In this scenario the use of Precision Agriculture (PA) in the farm management, considering the spatial variability for maximizing economic return and minimizing the risk of damage to the environment can be decisive. However, the adoption of PA by Brazili... R.Y. Inamasu, A.C. Bernardi |
4. Optimizing Site-Specific Adaptive Management Using A Probabilistic Framework: Evaluating Model Performance Using Historic DataAgricultural producers are tasked with managing crop yield responses to nitrogen (N) within systems that have high levels of spatial (biophysical), climatic, and price uncertainty. To date, the outcome of most variable rate application (VRA) research has focused on the spatial dimension, proposing optimal fertilizer prescription maps that can be applied year after year. However, temporally static prescriptions can result in suboptimal outcomes, particularly if they do... L.J. Rew, B.D. Maxwell, P.G. Lawrence |
5. Sustainable Grain Production With Continuous Improvements And Lean ProductionFew farmers are dedicated to critically examine their production processes. When something needs to be improved, the focus is on production with a concentration on the biological. But the profitability of a company is created by the production (what I do) and organization (how I do it). Agricultural advisory services are well developed in Sweden with services related to biological production (crop production planning, soil mapping, etc.) but there are no corresponding activities... B. Sundström, H. Åström, A. Rydberg, J. Olsson |
6. Evaluating Decision Systems For Using Variable Rates In Planting SoybeanIncreased interest in managing seeding rates within soybean fields is being driven by the advances in technologies and the need to increase productivity and economic returns. A wealth of previous research was focused on studying how different seeding rates affect soybean yields at small-plot scales. However, little is known how different site-specific factors influence the responsiveness of soybean to higher or lower plant population densities at field levels, especially across geographi... P. Reeg, P.M. Kyveryga, T.A. Mueller |
7. Adoption Of Precision Agriculture In Sweden – The Case Of Soil MapsAgriculture is facing great challenges in a world of changing climate and increased responsibility to find sustainable solutions to problems on both a local and a global scale, while agriculture at the same time faces higher costs for many inputs. Making decisions under such complex conditions is a delicate task. Precision agriculture is considered by many people as a tool to improve the efficiency of use of inputs and thereby improve resource utilization and reduction... J. Lindblom, C. Lundström, M. Ljung, A. Jonsson |
8. Factors Related To Adoption Of Precision Agriculture Technologies In Southern BrazilThe adoption of technologies which allow the increase of food production with improving quality in addition to reduce the foot prints in the environment is important for agribusiness development. Precision Agriculture (PA) stands out as an option to aid the achievement of these goals. Brazil plays an important role to supply agricultural products and to demand technologies. However, research has focused on technical and economic implementation of PA technologies. Therefore, more informat... A.A. Anselmi, L.C. Federizzi , C. Bredemeier, J.P. Molin |
9. Sustainable Use Of Irrigation WaterThe water footprint of irrigation systems can be reduced significantly by combining data from Electromagnetic (EM) soil survey with variable rate technology on irrigators. Variable Rate Irrigation (VRI) is providing annual irrigation water savings of between 25 -50% on farms throughout NZ. Flow-on benefits include reduced pumping costs, improved crop yields and soil health along with reduced nutrients leaching to groundwater. ... C. Mackenzie |
10. Economically Optimized Site Specific Nitrogen Application Using Data Mining ToolsAgricultural production in terms of economic and environmental demand requires increasingly efficient utilization of resources. Excessive use of nutrients may cause leaching, whereas deficits could lead to impediments in tapping full yield potential. Due to heterogeneity of fields, small-scale application of fertilizer provides means to encounter challenges that could arise and to improve resource efficiency. As part of an ongoing research project, we have investigated the abilit... P. Wagner, B. Burges |
11. Conditioning Factors For Decision-Making Regarding Precision Agriculture Techniques UsageThe eventual goal of using the techniques of precision agriculture (described as inputs applied at varied rates) is to get one of the following results: (a) lowering cost by reducing inputs, (b) decreasing the pollution of water, soil and the atmosphere and (c) increasing agricultural productivity by the more efficient use of inputs. However, studies on these techniques do not reach similar conclusions. This could be expected, since the effectiveness of these techniques would de... H.L. Burnquist, C.C. Costa |
12. Economics Of Site Specific Liming - Comparison Of On-The-Go And Grid-Based Soil Sampling To Determine The Soil pHAn important base for adequate liming is the recording of the soil pH. Several studies indicated a large heterogeneity of soil pH within fields. Recently technological improvements facilitate an on-the-go determination of the soil pH in a much higher sampling density compared to the conventional, time consuming and costly laboratory method. The “Veris soil pH sensor” allows georeferenced on-the-go mapping of the soil pH. But the “Veris soil pH sensor” and... T. Leithold, P. Wagner |
13. DTE – A Method Which Integrates Statistical Analysis With Economic Evaluation In Large Area Of Type 23 Experiments.Plant production is governed by certain, well-defined cultivation recommendations, especially important when quality standards imposed by contract agreements are to be met. Due to technical and economic conditions, a farmer is not always able to adhere to such recommendations in practice, but at the same time changes on the farm produce market (progress in plant breeding and mechanization of field work, new agrochemicals, effective microorganisms, etc) enforce producers to eithe... A. Imiolek, M. Imiolek |
14. Value Of Connectivity In Rural Areas: Case Of Precision Agriculture DataThe introduction of precision agricultural technologies in the early 1990’s was made possible through the utilization of global positioning system (GPS). However, unlike GPS which has worldwide coverage allowing field-level precision agricultural activities to occur. Collecting spatial and machinery data into a repository efficiently is not currently feasible in real-time due to lack of broadband and wireless connectivity in many rural areas even in developed counties. Lac... T. Griffin, T. Mark |
15. World Patent Map Analysis Of Mechanization Technologies Relatitng To Rice ProductionPatents comprise a unique source for technological knowledge. They are considered to be a good proxy for invention skills, R&D activities and for the scope of technological innovation of countries, regions, sectors and firms. Rice is one of the main field crops. The research focuses on patent mechanization technologies of soil working, planting and harvesting of rice production. Based on DWPI patent database and TI patent analysis software. The temporal examination by publication yea... X. Wang, Y. Hu, Z. Yi |
16. Introducing Precision Agriculture To High School Students In AustraliaThere is a growing need for tertiary qualified graduates in the Australian agricultural industry with only 7% of those employed in the sector holding a tertiary qualification compared to over 25% for the national workforce. With the need to greatly increase food and fibre production to feed and clothe a growing global population, and the adoption of precision agriculture technologies playing a huge part in this task, it is worrying that the demand for tertiary courses in agriculture in A... M.G. Trotter, A.M. Cosby |
17. Precision Agriculture As Bricolage: Understanding The Site Specific FarmerThere is an immediate paradox apparent in precision farming because it applies all of it ‘s precision and recognition of variability to the land, yet operates under the assumption of idealism and normative notions when it comes to considering the farmer. Precision Agriculture (PA) systems have often considered the farmer as an optimiser of profit, or maximiser of efficiency, and therefore replaceable with mathematical constructs, so that although at the centre of dec... I.J. Yule, B.A. Wood |
18. USA Corn Farm Profits And Adoption Of Precision AgricultureDemand for high-yielding, high-profit agricultural production practices is particularly strong among U.S. corn producers. Precision agriculture and its suite of information technologies allow farm operators to fine-tune their production practices and could decrease input costs and increase yields by providing a level of detailed within-field information not previously available. Technologies such as soil and yield mapping using a global positioning system (GPS), GPS tractor g... D. Schimmelpfennig |
19. 25 Years Precision Agriculture in Germany - a RetrospectiveIt all started with the availability of Global Positioning Systems for civil services in 1988. In the same year variable rate applications of fertilizers were demonstrated in northern Germany and Denmark, which were globally the first of their kind and introduced a new era of agricultural production. The idea of Computer Aided Farming (CAF) was born. Only one year later the first yield maps were established. In 1992 at the Soil Specific Crop Management Workshop in Bloomington, Minnesota which... H. Lilienthal, E. Schnug, S. Haneklaus |
20. Development of a Small Tracking Device for Cattle Using IoT TechnologyThe US is the largest producer of beef in the world. Last year alone, it produces nearly 19% of the world’s beef. This translate to about almost $90 billion in economic impact in the country. Aside from being a producer, the US also consumed more than 26 billion pounds of beef which have a retail value of the entire beef industry to more than $74B. For this level of production and consumption, each rancher in the US must produce a herd size of at least 100 or more to sustain the c... J.M. Maja, A.K. Blocker, E.G. Stuckey, S.G. Sell, G. Tuttle, J. Mueller, J. Andrae |
21. Detection and Monitoring the Risk Level for Lameness and Lesions in Dairy Herds by Alternative Machine-Learning AlgorithmsMachine-learning methods may play an increasing role in the development of precision agriculture tools to provide predictive insights in dairy farming operations and to routinely monitor the status of dairy cows. In the present study, we explored the use of a machine-learning approach to detect and monitor the welfare status of dairy herds in terms of lameness and lesions based on pre-recorded farm-based records. Animal-based measurements such as lameness and lesions are time-consuming, expen... D. Warner, R. Lacroix, E. Vasseur, D. Lefebvre |
22. The Animal Welfare of Dairy Cows Housed in Free-Stall Barn According to the Welfare Quality® Protocol: Good Feeding and Good Housing PrinciplesThe objective of the present study was to evaluate the animal welfare of dairy cows according to good feeding and good housing principles of the Welfare Quality® protocol. The protocol was applied to animals kept confined in a free-stall barn during their lactation. The farm was located in São João Batista do Glória, Minas Gerais state - Brazil. One hundred and one animals were evaluated (47 primiparous and 54 multiparous). The welfare measures were collected mostly t... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior |
23. The Correlation Between Criteria from Welfare Quality® Protocol Applied to Dairy Cows Housed in Free-Stall BarnThe objective of this study was to evaluate correlations between animal welfare criteria from the Welfare Quality® protocol applied to dairy cows. The protocol was applied on 47 primiparous and 54 multiparous dairy cows housed in a free-stall barn located in São João Batista do Glória, Minas Gerais - Brazil. Twelve welfare criteria were obtained from mostly animal-based welfare measures as proposed by the protocol. Pearson correlation coefficients (r) were calculated ... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior |
24. Evaluation of Nutrient Intake in Sheep Fed with Increasing Levels of Crambe Meal (Crambe Abyssinica Hoscht)The objective of this study was to evaluate the effects of increasing levels of crude protein (CP) substitution of the concentrate by CP of crambe meal (CM) (0, 25, 50 and 75% dry matter basis) on consumption of nutrients. Four rumen fistulated and castrated sheep (18 months old on average and initial body weight of 50 kg) were used distributed in a 4 x 4 Latin square design with 4 treatments and 4 experimental periods (repetitions). Diets were balanced to meet requirements for minimum gains ... K.K. De azevedo, D.M. De figueiredo, M.G. De sousa, G.M. Dallago, R.R. Silveira, L.D. Da silva, R.A. Santos |
25. Efficiency of Microbial Synthesis and the Flow of Nitrogen Compounds in Sheep Receiving Crambe Meal (Crambe Abyssinica Hochst) Replacing the Concentrade Crude ProteinThe objective of this study was to evaluate the effect of increasing levels (0, 25, 50, 75%) of crude protein substitution of the concentrate by crude protein of crambe meal on microbial protein synthesis and the flow of microbial nitrogen compounds in sheep. Four rumen fistulated sheep (18 months and initial average body weight of 50 kg) were distributed in a 4 x 4 Latin square design. Diets were balanced to meet the requirements for minimum gains, containing approximately 14% crude protein ... K.K. De azevedo, D.M. Figueiredo, G.M. Dallago, J.A. Vieira, R.R. Silveira, L.D. Da silva, R.A. Santos, L.N. Rennó, G.B. Pacheco |
26. On-Farm Experimentation and Decision-Support WorkshopThis 3-hour workshop discusses the requirements, methods and theories that may be used to assist in making optimal crop management decisions. The first part will focus on on-farm experimentation (OFE): 1) organization and benefits of OFE; 2) social processes and engagement; 3) designs, data and statistics. The second part will demonstrate how to generate insights applicable at the individual farm level using results from research trials collected in a diversity of contexts. Data sharing, meta... S. Cook, M. Lacoste, F. Evans, N. Tremblay, V. Adamchuk |
27. Economic Potential of RoboWeedMaps - Use of Deep Learning for Production of Weed Maps and Herbicide Application MapsIn Denmark, a new IPM ‘product chain’ has been constructed, which starts with systematic photographing of fields and ends up with field- or site-specific herbicide application. A special high-speed camera, mounted on an ATV took sufficiently good pictures of small weed plants, while driving up to 50 km/h. Pictures were uploaded to the RoboWeedMaps online platform, where appointed internal- and external persons with agro-botanical experience executed ‘virtual field ... P. Rydahl, O. Boejer, N. Jensen, B. Hartmann, R. Jorgensen, M. Soerensen, P. Andersen, L. Paz, M.B. Nielsen |
28. A Passive-RFID Wireless Sensor Node for Precision AgricultureAccurate soil data is crucial for precision agriculture. While existing optical methods can correlate soil health to the gasses emitted from the field, in-soil electronic sensors enable real-time measurements of soil conditions at the effective root zone of a crop. Unfortunately, modern soil sensor systems are limited in what signals they can measure and are generally too expensive to reasonably distribute the sensors in the density required for spatially accurate feedback. In thi... P.J. Goodrich, C. Baumbauer, A.C. Arias |
29. Development of a Granular Herbicide Spot Applicator for Management of Hair Fescue (Festuca Filiformis) in Wild Blueberry (Vaccinium Angustifolium)Hair fescue has quickly become the pest of greatest concern for the wild blueberry industry. This is largely due to its ability to outcompete wild blueberry for critical resources including water, nutrients and most importantly space. In Nova Scotia, between 2001 and 2019, hair fescue had increased in field frequency from 7% to 68% and in field uniformity from 1.4% to 25%. This rapidly spreading and economically destructive weed is likewise a significant challenge to manage, with only a s... C. Maceachern, T. Esau, Q. Zaman |
30. Using Prescription Maps for in Field Evaluations of Parameteres Affecting Spraying Accuracy of Self-propelled SprayerWeed presence continues to reemerge year over year, chemical costs continue to increase, and chemical usage continuing to face increasing government oversight, are just a few of the challenges that site-specific weed management intends to address by minimizing wasted application of chemicals and reducing environmental load of active ingredients. Thus, sprayer system manufacturers have developed precision spray systems that allow the individual spray nozzles to be controlled precisely. These s... J. Mayer, P. Flores, J. Stenger |
31. How Digital is Agriculture in South America? Adoption and LimitationsA rapidly growing population in a context of land and water scarcity, and climate change has driven an increase in healthy, nutritious, and affordable food demand while maintaining the current cropping area. Digital agriculture (DA) can contribute solutions to meet the demands in an efficient and sustainable way. South America (SA) is one of the main grain and protein producers in the world but the status of DA in the region is unknown. This article presents the results from a systematic revi... G. Balboa, L. Puntel, R. Melchiori, R. Ortega, G. Tiscornia, E. Bolfe, A. Roel, F. Scaramuzza, S. Best, A. Berger, D. Hansel, D. Palacios |
32. 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 |
33. Land Cover and Crop Types Classification Using Sentinel-2A Derived Vegetation Indices and an Artificial Neural NetworkDevelopments in remote sensing data acquisition capabilities, data processing and interpretation of ground-based, airborne and satellite observations have made it possible to couple remote sensing technologies and precision crop management systems. Land cover and crop types classification is a fundamental task in remote sensing and is crucial in various environmental and agricultural applications. Accurate and timely information on land cover and crop types is essential for land management, l... B. Bantchina |
34. Portable Soil EC - Development of an Electronic Device for Determining Soil Electrical ConductivityDecision-making in agriculture demands continuous monitoring, a factor that propels the advancement of tools within Agriculture 4.0. In this context, understanding soil characteristics is essential. Electrical conductivity (EC) sensors play a pivotal role in this comprehension. Given this backdrop, the core motivation of this research was developing an accessible and effective electronic device to measure the apparent EC of the soil. It provides features like geolocation, recording of the dat... C.L. Bazzi, L.A. Rauber, W.K. Oliveira, R. Sobjak, K. Schenatto, L. Gebler, L.M. Rabello |
35. 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 |
36. Integrating Nonlinear Models and Remotely Sensed Data to Estimate Crop Cardinal DatesCrop planting and harvest dates are a major component affecting agricultural productivity, risk, and nutrient cycling. The ability to track these cardinal dates allows researchers to investigate strategies to manage risk and adapt to climate change. This study was conducted to determine whether nonlinear statistical models combined with remotely sensed data from satellites can be used to estimate planting and harvest dates. Time of planting and harvest were reported by farmers for 16 commerci... C.L. Dos santos, F. Miguez, L. Puntel, D. Bullock |
37. Delineation of Yield Zones Using Optical and Radar Remote SensingIdentifying yield zones in agricultural areas is essential for efficient resource allocation, operational optimization, and decision-making. While optical remote sensing is widely used in precision agriculture, the interest in radar remote sensing data, notably from the Sentinel-1 Synthetic Aperture Radar (SAR), has increased due to its operation in the C-band frequency, capturing data through cloud cover and the availability of free data. The main objective of this study was to evaluate ... I.A. Da cunha, H. Oldoni, D.D. Melo, L.R. Amaral |
38. Influence of Ground Control Points and Processing Parameters on UAS Image Mosaicking for Plant Height EstimationDigital surface models (DSMs) and 3D point clouds, generated using overlapping images from unmanned aircraft systems (UASs), are often used for plant height estimation in phenotyping and precision agriculture. This study examined the effects of the quantity and placement of ground control points (GCPs) and image processing parameters on the creation of DSMs and 3D point clouds for plant height estimation. A 2-ha field containing multiple experimental plots with four crops (corn, cotton, ... C. Yang, H. Zhao, W. Guo, J. Zhang, C. Suh, B.K. Fritz |
39. 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 |
40. Dynamic Management Zones for Real-time Precision Agriculture OptimizationPrecision agriculture is an evolving management approach aimed at optimizing resource utilization, enhancing financial returns, and mitigating environmental impacts. The dynamic nature of agricultural conditions throughout a growing season necessitates the integration of innovative remote sensing and precision agriculture techniques. This research explores the creation of dynamic management zones (DMZ) that adapt in real-time to evolving soil and crop conditions. This study focuses on the est... A.H. Rabia, E. Eldeeb |
41. Comparative Analysis of Different On-the-go Soil Sensor SystemsThis study is part of the field of precision agriculture. This management mode is one of the great revolutions in the agriculture field, and it means better management of farm inputs such as fertilizers, herbicides, and seeds by applying the right amount at the right place and at the right time. To succeed in this, we should dispose of a tool that allows a precise assessment of the soil’s physical state. Thus, on-the-go soil sensors can be used as a creative tool to gain bette... H. Moulay, B. Arnall, S. Phillips |
42. The Evaluation of NDVI Response Index Consistency Using Proximal Sensors, UAV and SatellitesThe Response Index NDVI (RINDVI) is described as the response of crops to additional nitrogen (N) fertilizer. It is calculated by dividing the NDVI of the high-N plot (N-rich strip) by the NDVI of the zero-N plot or farmer's practice where less pre-plant N was applied (Arnall and al., 2016). RI values are used to predict yield and monitor top dress N fertilization. Many research has been carried out to d... S. Phillips, B. Arnall, M. Maatougui |
43. A Fusion Strategy to Map Corn Crop ResiduesAccess to post-harvest residue coverage information is crucial for agricultural management and soil conservation. The purpose of this study was to present a new approach based on an ensemble at the decision level for mapping the corn residue. To this end, a set of Landsat 8 imagery and field data including the Residue Cover Fraction (RCF) of corn (149 samples), were used. Firstly, a map of common spectral indices for RCF modeling was prepared based on the spectral bands. Then, the efficiency ... S. Fathololoumi, M.K. Firozjaei, A. Biswas, P. Daggupati |
44. UAV-based Phenotyping of Nitrogen Responses in Winter Wheat: Grain Yield and Nitrogen Use EfficiencyIn the face of escalating global demand for wheat, influenced by burgeoning populations and changing consumption patterns, a profound understanding of determinants like precision nutrient management becomes indispensable. In an on-farm experiment conducted at the Dürnast Research Station in southern Bavaria from 2022 to 2023, we investigated the effects of nitrogen (N) treatments on 18 European winter wheat (Triticum aestivum) cultivars. The field trial design encompassed three dist... J. Zhang, K. Yu |
45. 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 |
46. 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 |
47. Botanix Explorer (BX1): Precision Plant Phenotyping Robot Detecting Stomatal Openings for Precision Irrigation and Drought Tolerance ExperimentsUnder drought conditions, the kidney-shaped organs on the epidermal surface of plants, called stomata, are crucial to plant health. During transpiration, the stomata, which resemble pores, open and close. When the rate of photosynthesis is balanced, plants can withstand droughts by decreasing their stomatal transpiration. Drought-stressed plants are characterized by a higher number of open stomata. Measuring the pore aperture ratio is essential for precisely quantifying the degree of stomatal... S. Gummi, J.O. Kemeshi, Y. Chang |
48. 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 |
49. Growth Analysis on Cotton Using Unoccupied Aerial Systems (UAS) Based Multi-temporal Canopy FeaturesThe use of Unoccupied Aerial Systems (UAS) is rapidly evolving to generate imagery to determine crop growth patterns. A field experiment was conducted with thirty cotton varieties in 2016 and forty-two cotton varieties in 2021. The main objectives were (i) to perform growth analysis by using Canopy Cover (CC) and Canopy Height (CH) measurements obtained from UAS, (ii) to extract growth parameters from CC and CH data, (iii) to assess the relationship between the yield of co... S. Palla, M. Bhandari |
50. 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 |
51. 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 |
52. Airborne Spectral Detection of Leaf Chlorophyll Concentration in Wild BlueberriesLeaf chlorophyll concentration (LCC) detection is crucial for monitoring crop physiological status, assessing the overall health of crops, and estimating their photosynthetic potential. Fast, non-destructive, and spatially extensive monitoring of LCC in crops is critical for accurately diagnosing and assessing crop health in large commercial fields. Advancements in hyperspectral remote sensing offer non-destructive and spatially extensive alternatives for monitoring plant parameters such as L... K. Barai, C. Ewanik, V. Dhiman, Y. Zhang, U.R. Hodeghatta |
53. Relationship Between Water Use Efficiency, Daily Stomatal Conductance Trend and Evaporation of Maize and Soybean CropsWater Use Efficiency (WUE) represents the biomass production per unit of water and is commonly affected by temperature, carbon dioxide concentration, and water availability. Plants regulate the water transpiration efficiency through the opening and closing of stomata. Farmers can save water and maintain yield by improving crop's WUE during the period of drought through proper field management. The calculation of WUE requires the information of crop weight and irrigation volume, which is d... J. Zhang, N. Chamara, G. Bai, Y. Ge |
54. 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 |
55. Comparing Hyperspectral and Thermal UAV-borne Imagery for Relative Water Content Estimation in Field-grown SesameSesame (Sesamum indicum) is an irrigated oilseed crop, and studies on its water content estimation are sparred. Unmanned aerial vehicle (UAV)-borne imageries using spectral reflectance as well as thermal emittance for crops are an ample source of high throughput information about their physiological and chemical traits. Though several studies have dealt with thermal emittance to assess the crop water content, evaluating its relation to the plant’s solar reflectance is limi... M. Sahoo, R. Tarshish, V. Alchanatis , I. Herrmann |
56. 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 |
57. Yield Monitoring System for Radish and Cabbage Under Korean Field ConditionsYield monitoring is considered an essential tool to optimize resource utilization and provide an accurate assessment of crops for drylands. The objective of this study was to assess mass-based and volume-based yield monitoring under laboratory-simulated and field conditions for cabbage and radish. During the experiment, impact plate angles, conveyor speeds, and falling heights were systematically varied to investigate the effects on cabbage and radish yield during harvesting. Digital filterin... M. Gulandaz, M. Kabir, K. Shafik, S. Chung |
58. Predicting, Mapping, and Understanding the Drivers of Grain Protein Content Variability – Utilising John Deere’s New Harvestlab 3000 Grain Sensing SystemGrain protein content (GPC) is a key determinant of the prices that grain growers receive, and the rising cost of production is shifting management focus towards optimising this to maximise return on investment. In 2023, John Deere released the HarvestLab 3000TM Grain Sensing system in Australia for real-time, on-the-go measurement of protein, starch, and oil values for wheat, barley, and canola. However, while the uptake of these sensors is increasing, GPC maps are not available f... M.J. Tilse, P. Filippi, T. Bishop |
59. 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 |
60. The Role of Imaging Spectroscopy in Monitoring Soil Quality for Precision AgricultureImaging Spectroscopy (IS) is a key application in precision agriculture, offering insights into soil quality spatiotemporal variability. This technology's integration into soil quality mapping enables farmers and agricultural managers to make decisions that elevate efficiency, productivity, and sustainability within farming operations. With ongoing advancements in remote sensing technology, the role of IS in precision agriculture is poised for further expansion, promising enhanced benefit... T. Paz kagan |
61. 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 |
62. 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 |
63. Automated Pipeline for Research Plot Extraction and Multi-polygon Shapefile Generation for Phenotype and Precision Agriculture ApplicationsThe plant breeding community increasingly adopt remote sensing platforms like unmanned aerial vehicles (UAVs) to collect phenotype data on various crops. These platforms capture high-resolution multi-spectral (MS) image data during extensive field trials, enabling concurrent evaluation of hundreds of plots with diverse seed varieties and management practices. Currently, the plant breeders rely on manual and intricate data extraction, processing, and analysis of high-resolution imagery to draw... A. Sharda, A. Dua, W. Schapaugh, R. Hessel |
64. Evaluation of the Effect of Different Herbicide Treatments by Using UAV in Maise (Zea mays L.) Cultivation – First Experiences in a Long-term Experiment at Széchenyi István University, HungaryAs part of the Green Deal, the European Union has set a goal to reduce the use of chemical pesticides by 50 percent until 2030. To achieve this goal, in addition to reducing the amount of pesticide used, attention must also be paid to monitoring the temporal and spatial effects of pesticides on weeds during the cultivation of various crops. Hence, Syngenta Ltd., collaborating with researchers, aimed to monitor the effect of five different types of herbicides by UAV in two tillage treatments (... I.M. Kulmany, B. Horváth, G. Kukorelli, S. Zsebő, D. Stencinger, Z. Borbás, R. Pecze, L. Bede, Z. Varga, A. Kósa, G. Pinke, Z.K. Hashim, G. Hegedűs, J.A. Abdinoor, G.S. Agampodi |
65. 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 |
66. 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 |
67. 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 |
68. Detecting Nitrogen Deficiency and Leaf Chlorophyll Content (LCC) Using Sentinel-2 Vegetation IndicesLeaf chlorophyll content (LCC) is a significant indicator of photosynthetic performance and development status of plants. Remote sensing of crop chlorophyll often serves as a basic tool of crop nitrogen fertilization recommendation. The study's objective is to see how remote sensing can better monitor the growth difference of crops, such as LCC. In this study, we investigated the performance vegetation indices in (1) detecting the responses of wheat growth to nitrogen deficiency, and (2) ... X. Xu, A. Mokhtari, K. Yu |
69. Using Remote Sensing to Evaluate Cover Crop Performance and Plan Variable Rate ManagementThe adoption of cover crops (CC) in row-crop production, particularly in states like Indiana, has surged due to their recognized benefits in nutrient scavenging, soil health improvement, and erosion prevention. However, the spatial and temporal dynamics of CC performance pose challenges for efficient assessment and management. Traditional methods of quantifying CC production involve labor-intensive and time-consuming processes, creating a lag between data collection and decision-making for fa... S.A. Rubaino sosa, D. . Quinn, S. Armstrong |
70. Evaluating the Impact of Vegetation Indices on Plant Nitrogen Uptake Prediction: a Comparative Study of Regression Models at Various Growth StagesNitrogen and water play crucial roles in impacting both the health and yield of corn crops. However, their demands vary under different soil and weather conditions. Unfortunately, current nitrogen management practices in irrigated fields in the state of Georgia overlook this variability. Thus, this oversight may lead to insufficient nitrogen application, causing plant stress or excessive nitrogen application that can lead to environmental impact. To address this challenge, a precise asses... B. Ghimire, L. Lacerda, T. bourlai |
71. 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 |
72. Accurately Mapping Soil Profiles: Sensor Probe Measurements at Dense Spatial ScalesProximal sensing of soil properties has typically been accomplished using various sensor platforms deployed in a continuous sensing mode collecting data along transects, typically spaced 10-20 meters apart. This type of sensing can provide detailed maps of the X-Y soil variability and some sensors provide an indication of soil properties within the profile, however without additional investigations the profile is not delineated precisely. Alternatively, soil sensor probes can provide de... T. Lund, E. Lund, C.R. Maxton |
73. Enhancing Nutrient-related Stress Detection: High Throughput Phenotyping and Image Analysis for Improved PrecisionIn the 21-century agriculture has the unique responsibility to provide food, fuel, fiber and feed for the growing population under the stress of climate change and diminishing natural resources. A feat that will take considerable change to the sustainability of such practices. One of which is the idea of assessing phenotypic expression of complex traits in response to environmental factors. This idea elevates the use of phenotyping to quantitatively monitor stress manifestation. ... K.J. Bathke, Y. Ge, S.D. Choudhury, J.D. Luck |
74. 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 |
75. Estimating Water and Nitrogen Deficiency in Corn Using a Multi-parameter Proximal SensorThe Crop Circle Phenom (CCP) is an innovative integrated proximal sensor that can be potentially used to perform in-season diagnosis of nitrogen and water status. In addition to measuring spectral reflectance in several bands including the red, red edge, and near-infrared wavelengths, the CCP can also measure canopy and air temperatures and provides several parameters that can be associated with chlorophyll content, crop vigor, and water status. These capabilities differentiate the CCP from o... L. Lacerda, Y. Miao, V. Sharma, A. E. flores, A. Kechchour, J. Lu |
76. 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 |
77. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote SensingFor irrigated corn fields, how to optimize nitrogen (N) and irrigation simultaneously is a great challenge. A promising strategy is to use remote sensing to diagnose corn N and water status during the growing season, which can then be used to guide in-season variable rate N application and irrigation management. The objective of this study was to evaluate the effectiveness of UAV multispectral and thermal remote sensing in simultaneous diagnosis of corn N and water status. Two field experimen... Y. Miao, A. Kechchour, V. Sharma, A. Flores, L. Lacerda, K. Mizuta, J. Lu, Y. Huang |
78. 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 |
79. Field Mapping for Aflatoxin Assessment in Peanut Crops Using Thermal ImageryAflatoxin is a toxic carcinogenic compound produced by certain species of Aspergillus fungi, which has a significant impact on peanut production. Aflatoxin levels above a certain threshold (20 ppb in the USA and 4 ppb in Europe) make peanuts unsuitable for export, resulting in significant financial losses for farmers and traders. Unmanned Aerial Vehicles (UAVs) are becoming increasingly popular for remote sensing applications in agriculture. Leveraging this advancement, UAV-based thermal imag... S. Shrestha, L. Lacerda, G. Vellidis, C. Pilcon, S. Maktabi, M. Sysskind |
80. 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 |
81. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming ContextThe increasing expansion of irrigated almond orchards in regions of southeast Spain, facing water scarcity, underscores the need for a more effective and precise monitoring of the crop water status to optimize irrigation scheduling and improve crop water use efficiency. Remote and proximal sensing, combining visible, multispectral and thermal capabilities at different scales allows to estimate water needs, detect and quantify crop water stress, or identify different productivity zones within ... |
82. 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 |
83. 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 |
84. 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 |
85. Predicting Soil Cation Exchange Capacity from Satellite Imagery Using Random Forest ModelsCrop yield variability is often attributed to spatial variation in soil properties. Remote sensing offers a practical approach to capture soil surface properties over large areas, enabling the development of detailed soil maps. This study aimed to predict cation exchange capacity (CEC), a key indicator of soil quality, in the agricultural fields of the Lower Mississippi Alluvial Valley using digital soil mapping techniques. A total of 15,586 soil samples were collected from agricultural field... I. Muller, J. Czarnecki, M. Li, B.K. Smith |
86. 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 |
87. 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 |
88. 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 |
89. 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 |
90. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in AlabamaHarvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen dec... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa souza, A. Sanz-saez, S. Luns hatum de almeida , C. Pilcon, G. Vellidis |
91. Exploring Crop Suitability in Senegal Across Global Warming Scenarios: an In-silico ApproachFood production systems in Africa are fragile and vulnerable to climate change. In this context, rising temperatures are the primary cause of the anticipated negative climate change impacts on crop yields. Future yield reductions poses a challenging setting for smallholders to attain self-sufficiency, but new opportunities for managing the risk via implementationof decisions towards mitigate these negative effects from an economic, nutritional, and productive standpoint. Therefore, the object... A. Carcedo, I. Ciampitti |
92. Rapid Assessment of Yield Using Machine Learning Models and UAV Multispectral Imagery for Soybean Breeding PlotsAdvances in precision agriculture in data collection, crop monitoring, screening, and management over the 10-15 years are revolutionizing on-farm agricultural research trials. In crop breeding plots, this approach is called "High Throughput Phenotyping", which uses innovative technology to extract phenotypic data for large populations. Remote sensing has become one of the commonly used platforms for rapid acquisition of imagery data at spatial and temporal scale. Particularly, the u... A. Dua, A. Sharda, W. Schapaugh, R. Hessel, S. Rai |
93. Predicting Soil Chemical Properties Using Proximal Soil Sensing Technologies and Topography Data: a Case StudyUsing proximal soil sensors (PSS) is widely recognized as a strategy to improve the quality of agricultural soil maps. Nevertheless, the signals captured by PSS are complex and usually relate to a combination of processes in the soil. Consequently, there is a need to explore further the interactions at the source of the information provided by PSS. The objectives of this study were to examine the relationship between proximal sensing techniques and soil properties and evaluate the feasibility... F. Hoffmann silva karp, V. Adamchuk, P. Dutilleul, A. Melnitchouck, A. Biswas |
94. 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 |
95. 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 |
96. 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 |
97. 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 |
98. 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 |
99. Develop Portable Near-infrared Sensing Devices for Rapid Seed Moisture Measuring in Grass Seed CropsTo maximize harvest efficiency and seed yield, it is essential to harvest seed crops at appropriate timing. Seed moisture content (SMC) is the most reliable indicator of seed maturity and harvest timing in grass seed crops. Currently, to determine the SMC of a particular field, a minimum sample of 30 to 50 seed heads has to be collected from representative areas of the field and measured by wet and dry weights to calculate the SMC. The seeds must be either oven dried, microwave dried, or plac... J. Zhou |
100. 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 chlorophy... A.H. Rabia, D.G. Allam, E.F. Abdelaty, E.A. Abderaouf |
101. 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 |
102. Potential for Improving African Smallholder Cereal Farming Using Sentinel-2A Spectral ReflectanceCereal crops are critical for African smallholder farmers seeking to improve regional food availability, yet many struggle with low productivity from non optimal practices. This present study evaluated the possibility of using the satellite Sentinel-2 Multispectral Instrument data to inform management techniques tailored to African small-scale cereal farms’ local conditions. Improved practices maize, wheat, and rice plots were established respectively in Togo, Tunisia, and Tanzania... A. Biaou, S. Phillips |
103. 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 |
104. Premier Strategy Consulting - Sponsor Presentation... C. Zhu |
105. Veris Technologies - Sponsor PresentationVeris Technologies, Inc. designs, builds, and markets sensors and software for precision agriculture. ... T. Lund |
106. 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 |
107. 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 |
108. 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 |
109. North Dakota State University - Sponsor Presentation... L. Schumacher, P. Flores, R. Sun, A. Reinholz |