&amp;lt;i&amp;gt;Mission Planning and Ortho-mosaicking of UAS Imagery for Remote Sensing in Precision Agriculture on Winter Wheat and a Subsurface Drip Irrigated (SDI) Corn Field&amp;lt;/i&amp;gt;

Ford, Travis; Nagchaudhuri, Abhijit; Hartman, Christopher; Mitra, Madhumi

doi:10.13031/aim.201900795

Cited by 2 publications

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“…While farm employees are utilizing basic smart agricultural technologies on all production agricultural fields on campus, a specific 50-acre field that is under corn, soybean, and wheat rotation has been earmarked for systematic field trials, and data-driven research and analyses to study the benefits of using advanced precision farming technologies including drone imagery, prescription maps, variable rate sprayers, yield monitors and other intelligent implements. More recently a subsurface drip irrigation system has been installed on a 15-acre portion of this field for conducting field trials for both water and nutrient use efficiency [1][2][3].…”

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confidence: 99%

Grid Soil Sampling and Mapping Soil Phosphorus Distribution for an Extended Period on a Production Agricultural Field

Nagchaudhuri,

Mitra,

Ford

et al.

2022 ASEE Annual Conference &Amp; Exposition Proceedings

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Eastern Shore(UMES). Dr. Nagchaudhuri received his baccalaureate degree from Jadavpur University (India) with honors in mechanical engineering in 1983. Thereafter, he worked in a multinational industry for a little over three years before joining Tulane University as a graduate student in the fall of 1987. He received a master's degree from Tulane University in 1989 and a doctoral degree from Duke University in 1992. He is a member of the American Society for Mechanical Engineers (ASME), American Society for Engineering Education (ASEE), and, American Society for Agricultural and Biological Engineers (ASABE) and is actively involved in teaching and research in the fields of (i) robotics and mechatronics, (ii) remote sensing and precision agriculture, and,(iii) biofuels and renewable energy Madhumi Mitra (Professor)Dr. Mitra is a professor of Environmental Sciences at the University of Maryland Eastern Shore. Her research areas are in Bioenergy; Bioremediation; and Biosorption studies of aquatic plants.

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Grid Soil Sampling and Mapping Soil Phosphorus Distribution for an Extended Period on a Production Agricultural Field

Nagchaudhuri,

Mitra,

Ford

et al.

2022 ASEE Annual Conference &Amp; Exposition Proceedings

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UAS‐based multispectral imaging for detecting iron chlorosis in grain sorghum

Garcia‐Williams,

Starek,

Brewer

et al. 2024

Agrosystems Geosci & Env

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This study uses a small unmanned aircraft system equipped with a multispectral sensor to assess various vegetation indices (VIs) for their potential to monitor iron deficiency chlorosis (IDC) in a grain sorghum (Sorghum bicolor L.) crop. IDC is a nutritional disorder that stunts a plants’ growth and causes its leaves to yellow due to an iron deficit. The objective of this project is to find the best VI to detect and monitor IDC. A series of flights were completed over the course of the growing season and processed using Structure‐from‐Motion photogrammetry to create orthorectified, multispectral reflectance maps in the red, green, red‐edge, and near‐infrared wavelengths. Ground data collection methods were used to analyze stress, chlorophyll levels, and grain yield, correlating them to the multispectral imagery for ground control and precise crop examination. The reflectance maps and soil‐removed reflectance maps were used to calculate 25 VIs whose separability was then calculated using a two‐class distance measure, determining which contained the largest separation between the pixels representing IDC and healthy vegetation. The field‐acquired data were used to conclude which VIs achieved the best results for the dataset as a whole and at each level of IDC (low, moderate, and severe). It was concluded that the MERIS terrestrial chlorophyll index, normalized difference red‐edge, and normalized green (NG) indices achieved the highest amount of separation between plants with IDC and healthy vegetation, with the NG reaching the highest levels of separability for both soil‐included and soil‐removed VIs.

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<i>Mission Planning and Ortho-mosaicking of UAS Imagery for Remote Sensing in Precision Agriculture on Winter Wheat and a Subsurface Drip Irrigated (SDI) Corn Field</i>

Cited by 2 publications

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Grid Soil Sampling and Mapping Soil Phosphorus Distribution for an Extended Period on a Production Agricultural Field

Grid Soil Sampling and Mapping Soil Phosphorus Distribution for an Extended Period on a Production Agricultural Field

UAS‐based multispectral imaging for detecting iron chlorosis in grain sorghum

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