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Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
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Authors
Abdelaty, E.F
Abderaouf, E.A
Abdinoor, J.A
Adamchuk, V
Agampodi, G.S
Alchanatis, V
Allam, D.G
Amaral, L.R
Armstrong, S
Arnall, B
Arnall, B
Bai, G
Bantchina, B
Barai, K
Bathke, K.J
Bazzi, C.L
Bede, L
Bhandari, M
Bishop, T
Biswas, A
Biswas, A
Borbás, Z
Bourlai, T
Bullock, D
Chamara, N
Chang, Y
Choudhury, S.D
Chung, S
Costa Souza, J.B
Czarnecki, J
Daggupati, P
Dhiman, V
Dua, A
Dua, A
Dutilleul, P
E. Flores, A
Eldeeb, E
Ewanik, C
Fathololoumi, S
Filippi, P
Firozjaei, M.K
Flores, A
Flores, P
Fritz, B.K
Ge, Y
Ge, Y
Gebler, L
Ghimire, B
González Piqueras, J
Gulandaz, M
Gummi, S
Guo, W
Gómez-Candón, D
Hanyabui, E
Hashim, Z.K
Hegedűs, G
Herrmann, I
Hessel, R
Hessel, R
Hodeghatta, U.R
Hoffmann Silva Karp, F
Horváth, B
Huang, Y
Jiménez Castaño, V
KABIR, M
Kechchour, A
Kechchour, A
Kemeshi, J.O
Kukorelli, G
Kulmany, I.M
Kósa, A
Lacerda, L
Lacerda, L
Lacerda, L
Lacerda, L
Li, M
Lu, J
Lu, J
Luck, J.D
Lund, E
Lund, T
Lund, T
Luns Hatum de Almeida, S
López-Urrea, R
Maatougui, M
Maktabi, S
Maxton, C.R
Melnitchouck, A
Melo, D.D
Miao, Y
Miao, Y
Miguez, F
Mizuta, K
Mokhtari, A
Montoya Sevilla, F
Moulay, H
Muller, I
Oldoni, H
Oliveira, M.F
Oliveira, W.K
Ortiz, B.V
PHILLIPS, S
Palla, S
Paz Kagan, T
Pecze, R
Phillips, S
Pilcon, C
Pilcon, C
Pinke, G
Puntel, L
Pérez García, Y
Quinn, D.J
Rabello, L.M
Rabia, A.H
Rabia, A.H
Rai, S
Rauber, L.A
Reinholz, A
Rubaino Sosa, S.A
Sahoo, M
Sanz-Saez, A
Schapaugh, W
Schapaugh, W
Schenatto, K
Schumacher, L
Shafik, K
Sharda, A
Sharda, A
Sharma, V
Sharma, V
Shrestha, S
Smith, B.K
Sobjak, R
Stencinger, D
Suh, C
Sun, R
Sysskind, M
Sánchez Tomás, J
Sánchez Virosta, Ã
Tarshish, R
Tilse, M.J
Varga, Z
Vellidis, G
Vellidis, G
Xu, X
Yang, C
Yu, K
Yu, K
Zhang, J
Zhang, J
Zhang, J
Zhang, Y
Zhao, H
Zhoa, L
Zhou, J
Zsebő, S
da Cunha, I.A
dos Santos, C.L
Topics
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Oral
Poster
Year
2024
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Topics

Filter results37 paper(s) found.

1. Land Cover and Crop Types Classification Using Sentinel-2A Derived Vegetation Indices and an Artificial Neural Network

Developments 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

2. Portable Soil EC - Development of an Electronic Device for Determining Soil Electrical Conductivity

Decision-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

3. Integrating Nonlinear Models and Remotely Sensed Data to Estimate Crop Cardinal Dates

Crop 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

4. Delineation of Yield Zones Using Optical and Radar Remote Sensing

Identifying 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

5. Influence of Ground Control Points and Processing Parameters on UAS Image Mosaicking for Plant Height Estimation

Digital 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

6. Dynamic Management Zones for Real-time Precision Agriculture Optimization

Precision 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

7. Comparative Analysis of Different On-the-go Soil Sensor Systems

This 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

8. The Evaluation of NDVI Response Index Consistency Using Proximal Sensors, UAV and Satellites

The 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

9. A Fusion Strategy to Map Corn Crop Residues

Access 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

10. UAV-based Phenotyping of Nitrogen Responses in Winter Wheat: Grain Yield and Nitrogen Use Efficiency

In 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

11. Botanix Explorer (BX1): Precision Plant Phenotyping Robot Detecting Stomatal Openings for Precision Irrigation and Drought Tolerance Experiments

Under 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

12. Growth Analysis on Cotton Using Unoccupied Aerial Systems (UAS) Based Multi-temporal Canopy Features

The 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

13. Airborne Spectral Detection of Leaf Chlorophyll Concentration in Wild Blueberries

Leaf 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

14. Relationship Between Water Use Efficiency, Daily Stomatal Conductance Trend and Evaporation of Maize and Soybean Crops

Water 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

15. Comparing Hyperspectral and Thermal UAV-borne Imagery for Relative Water Content Estimation in Field-grown Sesame

Sesame (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

16. Yield Monitoring System for Radish and Cabbage Under Korean Field Conditions

Yield 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

17. Predicting, Mapping, and Understanding the Drivers of Grain Protein Content Variability – Utilising John Deere’s New Harvestlab 3000 Grain Sensing System

Grain 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

18. The Role of Imaging Spectroscopy in Monitoring Soil Quality for Precision Agriculture

Imaging 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

19. Automated Pipeline for Research Plot Extraction and Multi-polygon Shapefile Generation for Phenotype and Precision Agriculture Applications

The 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

20. 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, Hungary

As 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

21. Detecting Nitrogen Deficiency and Leaf Chlorophyll Content (LCC) Using Sentinel-2 Vegetation Indices

Leaf 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

22. Using Remote Sensing to Evaluate Cover Crop Performance and Plan Variable Rate Management

The 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

23. Evaluating the Impact of Vegetation Indices on Plant Nitrogen Uptake Prediction: a Comparative Study of Regression Models at Various Growth Stages

Nitrogen 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

24. Accurately Mapping Soil Profiles: Sensor Probe Measurements at Dense Spatial Scales

Proximal 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

25. Enhancing Nutrient-related Stress Detection: High Throughput Phenotyping and Image Analysis for Improved Precision

In 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

26. Estimating Water and Nitrogen Deficiency in Corn Using a Multi-parameter Proximal Sensor

The 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

27. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote Sensing

For 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

28. Field Mapping for Aflatoxin Assessment in Peanut Crops Using Thermal Imagery

Aflatoxin 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

29. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming Context

The 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 ...

30. Predicting Soil Cation Exchange Capacity from Satellite Imagery Using Random Forest Models

Crop 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

31. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in Alabama

Harvest 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

32. Rapid Assessment of Yield Using Machine Learning Models and UAV Multispectral Imagery for Soybean Breeding Plots

Advances 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

33. Predicting Soil Chemical Properties Using Proximal Soil Sensing Technologies and Topography Data: a Case Study

Using 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

34. Develop Portable Near-infrared Sensing Devices for Rapid Seed Moisture Measuring in Grass Seed Crops

To 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

35. Utilizing Thermal and RGB Imaging for Nutrient Deficiency and Chlorophyll Status Evaluation in Plants

As 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

36. Veris Technologies - Sponsor Presentation

Veris Technologies, Inc. designs, builds, and markets sensors and software for precision agriculture. ... T. Lund

37. North Dakota State University - Sponsor Presentation

... L. Schumacher, P. Flores, R. Sun, A. Reinholz