Ag and Natural Resources
GRI is using remote sensing and hyperspectral imagery among other technologies to develop research activities in the different sectors of agriculture and natural resource management. GRI researchers examine areas such as invasive species, agri-terrorism, site-specific crop management, and the strengthening of our rivers' levee systems.

A novel hyperspectral-based approach for identification of maize kernels infected with diverse Aspergillus flavus fungi
Near infrared hyperspectral imaging over the spectral range of 900–2500 nm was investigated for its potential to identify maize kernels inoculated with aflatoxigenic fungus (AF13) from healthy kernels and kernels inoculated with non-aflatoxigenic fungus (AF36). A total of 900 kernels were used with 3 treatments, namely, each 300 kernels inoculated with AF13, AF36 and sterile distilled water as control, separately. One hundred kernels from each treatment of 300 kernels were incubated for 3, 5 and 8 days, to obtain diverse samples. Based on the full mean spectra extracted from the same kernel side(s), the best mean overall prediction accuracies achieved were 96.3% for the 3-class (control, non-aflatoxigenic and aflatoxigenic) classification and 97.8% for the 2-class (aflatoxigenic-negative and -positive) classification using the partial least-squares discriminant analysis (PLS-DA) method. The 3-class and 2-class models using the full mean spectra extracted from different kernel sides had the best mean overall prediction accuracies of 91.5% and 95.1%. Using the most important 30, 55 and 100 variables determined by the random frog (RF) algorithm, the simplified type I-RF-PLSDA models achieved the mean overall prediction accuracies of 87.7%, 93.8% and 95.2% for the 2-class discrimination using different kernel sides’ information. Among the most important 55 and 100 variables, a total of 25 and 67 variables were consistently selected in the 100 random runs and were therefore used further for establishing the type II-RF-PLSDA models. Using these 25 and 67 variables, the type II-RF-PLSDA models obtained the mean overall prediction accuracies of 82.3% and 94.9% separately.
Research Document

A Rapid and Nondestructive Method for Simultaneous Determination of Aflatoxigenic Fungus and Aflatoxin Contamination on Corn Kernels
Conventional methods for detecting aflatoxigenic fungus and aflatoxin contamination are generally time-consuming, sample-destructive, and require skilled personnel to perform, making them impossible for large-scale nondestructive screening detection, real-time, and on-site analysis. Therefore, the potential of visible
Abstract Publication in A Journal of Food and Chemistr

Advection of Karenia Brevis Blooms from the FL Panhandle towards the MS Bight and Sound
Harmful Algal Blooms (HABs) of Karenia brevis have been documented along coastal waters of every state bordering the Gulf of Mexico (GoM). Some Gulf Coast locations, such as Florida and Texas, suffer from recurrent intense and spatially large blooms, while others such as Mississippi seem to rarely observe them. The main objective of this work is to understand the dynamics that led to the K. brevis bloom in Mississippi coastal waters in fall 2015. Blooms of K. brevis from the Florida Panhandle region are often advected westward towards the Mississippi-Alabama coast; however there is interannual variability in their presence and intensity in Mississippi coastal waters. The 2015 K. brevis bloom was compared to the 2007 Florida Panhandle K. brevis bloom, which showed a westward advection pattern, but did not intensify along the Mississippi coast. Cell counts and flow cytometry were obtained from the Mississippi Department of Marine Resources, Alabama Department of Public Health, Florida Fish and Wildlife Conservation Commission and The University of Southern Mississippi. Ocean color satellite imagery from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite was used to detect and delineate the blooms in 2007 and 2015.
Abstract and Document Site

Application of Structure from Motion Techniques in Late-season Corn Damage (UAS)
Green snap occurs when corn stalks are broken in high wind. Late in the season, green snap produces yield losses that are immediate and irreversible. Losses are proportional to the percentage of plants lost, thus estimation of damage extent is important for calculating economic loss. Unmanned aerial vehicles are capable of creating a 3D-model, called a digital surface model, of the crop canopy using structure from motion techniques. The objective of this study was to compare image- versus structure-based calculations of damaged area. The structure-based calculations were more reflective of the field assessment. While the latter approach showed promise, more development of protocols is needed for reliability and operational success.
Abstract Precision Agriculture

Aquatic Invasive Species- Habitat Suitability Modeling
GRI researchers are using Habitat Suitability Modeling which uses computer algorithms to manipulate data that create models to predict, control and narrow the expansive search area required for detection of new non-native species of likely avenues for the spread of existing plant populations. Researchers have found four ways to control aquatic invasive species. They include chemical, biological, physical and mechanical methods. These methods can control or eradicate invasive plant species in an area.
Email Contact

Cactus Moth Detection and Monitoring Network (CMDMN)
This website details the CMDMN program which relies on volunteers to monitor cactus populations and report observations. This is the first step of an Early Detection and Rapid Response (EDRR) approach. The data will be used to support modeling efforts to better predict likely locations for new pricklypear cactus and cactus moth and help guide surveys.

Comparing an Annual and a Daily Time-Step Model for Predicting Field-Scale Phosphorus Loss
A wide range of mathematical models are available for predicting phosphorus (P) losses from agricultural fields, ranging from simple, empirically based annual time-step models to more complex, process-based daily time-step models. In this study, we compare field-scale P-loss predictions between the Annual P Loss Estimator (APLE), an empirically based annual time-step model, and the Texas Best Management Practice Evaluation Tool (TBET), a process-based daily time-step model based on the Soil and Water Assessment Tool. We first compared predictions of field-scale P loss from both models using field and land management data collected from 11 research sites throughout the southern United States. We then compared predictions of P loss from both models with measured P-loss data from these sites. We observed a strong and statistically significant (p
Abstract Document

CONCORDE Meteorological Analysis (CMA) Data Guide
CONCORDE is the CONsortium for oil spill exposure pathways in COastal River-Dominated Ecosystems (CONCORDE), and is an interdisciplinary research program funded by the Gulf of Mexico Research Initiative (GoMRI) to conduct scientific studies of the impacts of oil, dispersed oil and dispersant on the Gulf
Abstract Document Oceanography Article Discuses CMA

Corn crop density assessment using texture analysis on visible imagery collected using unmanned aerial vehicles
Determining corn crop density on a large field is of tremendous value to monitor plant health and damages caused by hogs and deer. Texture modelling techniques are investigated to map three different densities (Low, Medium and High) on a corn field by using visible imagery collected using an Unmanned Aerial Vehicle (UAV).
Further Details

Cost Effective BMPs for Resilient Communities
This project developed a tool that will enable the development industry to design and build more resilient and sustainable communities through the inclusion of BMPs (Best Management Practices) in new commercial and residential construction.
Email Contact

Detecting Aflatoxin using Hyperspectral Imaging
Hyperspectral imaging is a way of seeing what is invisible to the human eye. GRI researchers are using this to detect biological and chemical toxins that contaminate crops. This is done by splitting the electromagnetic spectrum into many spectral bands, which expose hidden information invisible to the natural eye. The specific contaminant being studied is a fungal metabolite called aflatoxin. This lethal toxin is produced by a fungus called Aspergillus. It is a known carcinogen associated with liver and lung cancers in humans. Many external stresses cause the fungi to react but hot and humid weather conditions increase its production of aflatoxin that invades corn and other commodities. The goal is to help improve detection and accuracy.
Email Contact

Detection of Aflatoxin B1 on Corn Kernel Surfaces Using Visible-near Infrared spectroscopy: Journal of Near Infrared Spectroscopy. 1-11.
In this study, visible-near infrared spectroscopy over the spectral range of 400
Journal of Near Infrared Spectroscopy. 1-11.

Detection of Plant Parasitic Nematodes and Host Gene Expression Using Hyperspectral Reflectance and Management with VRT Applications
The objectives of this research include detecting spectral and directional reflectance of plants known to be infected with reniform nematode, correlating this data to hyperspectral reflectance data from actual field populations, initiating studies to detect nematode presence in other agricultural crops, and developing and evaluating liquid and granular variable rate nematicide applications. Development of nematode detection and variable rate technology systems for control of nematode populations would result in increased efficiency, higher profits, and optimized crop production with minimum input of nematicides and reduced environmental impacts.
Email Contact

Developing a Foundation for Analysis of Natural and Human-Induced Disturbances to Coastal Economies
This project focuses on the relationship between people and the ecosystems, resources, and hazards of the Gulf Coast. Because almost all human decisions are dependent on time, uncertainty (risk), cost, and expected benefits, this project can shed light on how the choices of coastal residents, businesses, and other entities are influenced by those characteristics unique to the coast. Furthermore, because economic analysis is always geared toward understanding the value of things and how these values influence decisions, this project will provide a wide range of cost and benefit estimates that can be utilized by decision-makers at all levels to make choices that improve the quality of life along the Northern Gulf Coast.
Email Contact

Developing New Strategies for Management of Invasive Aquatic Plants
GRI is developing new strategies for the management of invasive aquatic plants through research at our mesocosm tank facility on the campus of Mississippi State University. We are evaluating new aquatic herbicides, combinations of existing aquatic herbicides, and applying management techniques based on a new understanding of plant species life history. These projects may be proprietary; and funded by private industry, federal, state, and local government agencies, and nonprofit foundations.

Development and Validation of Geospatial Tools to Optimize Implementation of Precision Conservation
Conservation programs under the Farm Bill provide economic incentives for agricultural producers to divert marginally profitable land from production to targeted conservation practices. The adoption of conservation practices may depend on the profitability of program participation, relative to full production. Spatially explicit yield data, combined with production budgets, commodity prices, and program eligibility criteria can inform producers regarding the economical optimality of production vs. conservation. The objectives of this research are to develop decision support tools within ArcGIS that identify opportunities for implementation of conservation programs on agricultural landscapes, measure profitability of alternative programmatic enrollments vs. whole field production, and predict wildlife population benefits of these alternatives. This research will help producers to make informed economic decisions regarding land usage for conservation programs and crop production, benefiting both the farmer and native wildlife.
Email Contact

Development of a Water Budget for Tail-water Recovery Systems
Unsustainable groundwater use for agricultural irrigation has led to declining aquifer levels across the United States, necessitating implementation of water conservation practices. One conservation practice being implemented throughout the lower Mississippi River alluvial valley (LMAV) that collects and stores surface water for irrigation is a tailwater recovery (TWR) system. Accordingly, the overall objective of this study was to develop a water budget for TWR systems. Eight TWR systems were continuously monitored for water depth, allowing rates of water gain and loss to be quantified. Volumes of water movement were calculated based on change in water depth and system dimensions. Using water budgets derived from TWR systems the water volume was calculated and found to be gaining, except during months of irrigation. Extrapolating the water budget to all TWR systems shows a total offset of 15% of the annual groundwater deficit. Tailwater recovery system efficiencies show designs may be altered to improve the water savings and use of these systems.
Journal of Irrigation and Drainage OnlineSite ASCE Online SIte

Development of High Speed Dual Camera System for Batch Screening of Aflatoxin Contamination of Corn Using Multispectral Fluorescence Imaging
Aflatoxins are fungal toxins produced by . Food and feed crops contaminated with carcinogenic aflatoxins result in economic losses as well as potentially serious health issues. Grain elevators need to unload, on average, one 2.27 metric ton (MT) truckload every 2 min. Current sampling-based analytical chemistry methods for aflatoxin detection cannot meet these large throughput screening requirements. Therefore, a high-speed, batch screening system with reliable accuracy is needed. To develop a high-speed multispectral screening system, two high-performance cameras in conjunction with dual UV excitation sources and novel image processing software were used to collect fluorescence images of corn samples.
Abstract and Research

Dissolved organic matter and trace element variability in a blackwater-fed bay following precipitation
Highlights Dissolved organic matter compositions were used for source-tracking trace metals. Flux of As, Cu, U, PO4, and NO3 correlated with protein-like and soil-derived DOM. The trace element and DOM mobility was controlled by precipitation and discharge. Multivariate statistics revealed anthropogenic sources for the trace metals. Abstract Dissolved organic matter (DOM) often forms complexes with trace metals. The main objective of this study was to identify the sources of trace elements to a coastal bay that is fed by two blackwater rivers using DOM compositions. Surface water samples from twelve sites in Weeks Bay, Alabama were collected during four field trips and a bottom sediment sample was collected during one of the trips. Spectroscopic measurements in tandem with parallel factor analysis and multivariate statistics were used to derive DOM compositions and inductively coupled plasma mass spectrometry was used for determining trace metal concentrations. DOM chemistry and trace element concentrations together with precipitation and discharge, watershed land use and land cover data, and physicochemical parameters were used to determine the source of trace elements in the adjoining areas of the watershed to the bay and finally settling into the bay sediments.
Science Direct

Distribution and Management of Invasive Plant Species in the Ross Barnett Reservoir
The objectives of this research is to monitor and map invasive aquatic plant populations. Long term changes are recorded in the plant community of the Ross Barnett Reservoir and the management effectiveness of certain invasive plant species is assessed.

Earth Dams and Levees (EDLs) Sustainability
Research in using remote sensing to improve earth dam and levee sustainability has the potential to affect tens of millions of people who live or work behind levee-protected areas. MSU/GRI researchers in an international partnership are conducting research on multi-scale monitoring science to enable a sustainable future for the vast worldwide array of earth dam and levees. The research examines EDL critical infrastructure that provides flood protection, fresh water storage and renewable energy to developed and underdeveloped nations. This project is currently in year two and uses polarimetric and interferometric synthetic aperture radar (SAR) to examine earth deformations at a very small scale.

Effect of Photo-biodegradation and Biodegradation on the Biogeochemical Cycling of Dissolved Organic Matter across Diverse Surface Water Bodies
The objective of this research was to quantify the temporal variation of dissolved organic matter (DOM) in five distinct waterbodies in watersheds with diverse types of land use and land cover in the presence and absence of sunlight. The water bodies were an agricultural pond, a lake in a forested watershed, a man-made reservoir, an estuary, and a bay. Two sets of samples were prepared by dispensing unfiltered samples into filtered samples in 1:10 ratio (V/V). The first set was exposed to sunlight (10
Abstract and Research

Effects of Rainfall, Geometrical and Geomorphological Variables on Vulnerability of the Lower Mississippi River Levee System to Slump Slides
This study investigated the importance of rainfall and various geomorphological and geometrical factors to the vulnerability of earthen levees to slump slides. The study was performed using a database including 34 slump slides that occurred in the lower Mississippi River levee system from 2008 to 2009. The impact of rainfall within the six months prior to slide occurrence was studied for 23 slides for which an accurate occurrence date was available. Several variables were used to develop a logistic regression model to predict the probability of slump slide occurrence. The proposed model was verified for both slide and non-slide cases. The regression analysis depicts the impact of channel width, river sinuosity index, riverbank erosion, channel shape condition and distance to river. Excluding the sinuosity index, the impact of the other independent variables examined was found to be significant. Occurrence of riverbank erosion around the slide locations was the most significant predictor factor. A channel width of less than 1000 m was ranked as the second most significant variable. The proposed model can aid in locating high-risk areas on levees in order to take prompt protective measures, increase monitoring efforts and enable early response under emergency conditions.

Effects of Variation in Sweetpotato Development, Yield, and Quality
The field variability associated with sweetpotato growth habit presents a unique opportunity to use site-specific crop management techniques to accurately pinpoint best-growth implement practices for sweetpotatoes in individual fields. The objectives of this research are to use remotely sensed and ground-truthed data to construct maps that describe field variability, identify critical parameters that affect growth and development of sweetpotatoes, and investigate crop response to various producer inputs developed in management zones. The collection of these data will help validate a sensor-driven model-based decision support and risk tool that can be utilized by producers.
Email Contact

Enhanced Soils Mapping For Productive Capacity Assessments
This research uses geospatial technologies to create methodology used in defining soil management zones that address soil variability in distinct areas and identify the soil properties that limit crop production while increasing soil conservation. Determining appropriate soil management zones can lead to an increased profit by either increasing yield in areas of fields that are being underutilized or decreasing fertilization in areas of fields where maximum economic yield has already been attained. Moreover, robust and repeatable methodology for construction of management zones will provide an empirical basis for developing variable rate fertilizer prescriptions that optimize profitability and minimize off-site nutrient transport, thereby benefiting the producer, the public, and the environment.
Email Contact

Evaluation of a Synthetic Rainfall Model, P-CLIPER, for Use in Coastal Flood Modeling
With the projected increase in both tropical cyclone (TC) intensity and proportion of the global population living near the coast, adequate preparation to protect against TC flooding is in the economic interest of coastal cities worldwide. Numerical models that describe TC properties, e.g., storm surge and wind fields, are currently employed to simulate the component of flooding that results from seawater inundation of areas along the coast (i.e., saltwater flooding). However, without the inclusion of freshwater flooding, contributed by inland surface flow and direct precipitation, a total water level (TWL) system for TC flooding lacks a complete picture of the actual coastal flood levels. Working toward a true TWL system, this research investigates the efficacy of the simple and efficient parametric TC rainfall model P-CLIPER (PDF Precipitation-Climatology and Persistence) to provide historically representative TC rainfall to a TWL system. This research demonstrates the success of this novel use of P-CLIPER through calibration and validation to the Tar

Evaluation of Geospatial Tools to Map Dispersal of Invasive Aquatic Plants in Agroecosystems
This study validates new techniques of mapping and tracking the distribution and transport of invasive aquatic plants by using remote sensing technology to map known locations of these plants, sampling dispersal rates under normal and stormy weather conditions and modeling the output using ArcPro, and comparing these rates to those already recorded through GPS tracking. Gaining an understanding of how invasive aquatic weeds disperse through agricultural areas and creating a tool to reduce the negative effects these weeds have on agronomic crops is vital for the improvement in crop yields and the management of unwanted weed species invading otherwise healthy ecosystems.

Evaluation of the APEX Model to Simulate Runoff Quality from Agricultural Fields in the Southern Region of the U.S.
The Agricultural Policy Environmental eXtender (APEX) model has been widely applied to assess phosphorus (P) loss in runoff water and has been proposed as a model to support practical decisions regarding agricultural P management, as well as a model to evaluate tools such as the P Index. The aim of this study is to evaluate the performance of APEX to simulate P losses from agricultural systems to determine its potential use for refinement or replacement of the P Index in the southern region of the United States. Uncalibrated and calibrated APEX model predictions were compared against measured water quality data from row crop fields in North Carolina and Mississippi and pasture fields in Arkansas and Georgia. Calibrated models satisfactorily predicted event-based surface runoff volumes at all sites (Nash-Sutcliffe efficiency [NSE]

GIS for Aquatic Plant Management
Geographic Information Systems (GIS) have become the new tool for information management, planning and presentation for invasive aquatic plant management programs and is critical in every component of the program.

Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC)
GRI has partnered with the GCPO LCC to provide critical LCC research and computing capacity for LCC activities. As a research hub for the GCPO LCC, GRI has established over $4 million in cooperative agreements with the U.S. Fish and Wildlife Service to fund more than 20 different LCC research projects. This diverse research program includes exploration of ecosystem health, resilience to climate change and urbanization and interrelationships among species and their habitats.
Email Contact

Health and Productivity of Louisiana Salt Marshes
This study will allow the identification of hotspots of marsh degradation in Louisiana by evaluating marsh biophysical characteristics including distribution of chlorophyll content, green leaf area and green marsh canopy cover. This assessment of marsh health and productivity is due to the Deepwater Horizon oil spill. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images will be used to retrieve and map these characteristics across the coastal Louisiana salt marshes before and after the spill. The maps and tools produced from the study will be helpful to coastal managers across Louisiana as they evaluate and prioritize the marsh restoration effort which will take place due to the oil spill. Tangible map products will be generated for the first time that can quantitatively assess the effect of the restoration activities and speed of marsh ecosystem recovery.
Email Contact

Integrated Pest Management Systems and Resistance Management Using Geospatial Technologies
This research has evaluated the use of remote sensing technologies to detect and predict spatial distribution of weed populations for the purpose of designing site-specific herbicide prescriptions and monitoring the spread of herbicide resistant weed species. Associated spatial technologies have been used to generate guidelines for creation of site-specific harvest-aid, plant growth regulator, and insecticide prescriptions. A unique contribution of this research has been the development of novel statistical models that more fully characterize geographic, topographic, hydrological, edaphic, and producer-induced sources of variation in yield than previously understood. The research also highlights the immense complexity of spatial data collection, management, geoprocessing, and integration for decision support in site-specific agriculture. Outcomes of this study may increase efficiency and profitability, reduce the threat of off-target movement of residual herbicides in runoff to surface and groundwater, and reduce herbicide usage through precision applications.
Email Contact

Invasive Species Program
GRI researchers actively study invasive plants that take over agricultural and natural areas, with expertise for studies ranging from regional impacts through use of remote sensing and GIS, to cellular and molecular studies of plant uptake, and genetic composition. GRI brings together multidisciplinary research teams comprised of university and government researchers to address diverse questions on the management of invasive species.

Investigating the Correlation between Radar Backscatter and In Situ Soil Property Measurements
Utilizing remote sensing techniques to extract soil properties can facilitate several engineering applications for large-scale monitoring and modeling purposes such as earthen levees monitoring, landslide mapping, and off-road mobility modeling. This study presents results of statistical analyses to investigate potential correlations between multiple polarization radar backscatter and various physical soil properties. The study was conducted on an approximately 3 km long section of earthen levees along the lower Mississippi river as part of the development of remote levee monitoring methods. Polarimetric synthetic aperture radar imagery from UAVSAR was used along with an extensive set of in situ soil properties. The following properties were analyzed from the top 30
Abstract and Document

Land use and land cover control on the spatial variation of dissolved organic matter across 41 lakes in Mississippi, USA
While dissolved organic matter (DOM) is an important indicator of water quality, land use and land cover (LULC) of watersheds define the source, quality, and quantity of DOM delivered to a waterbody. This study examined the influence of various LULC classes in the spatial distribution of DOM in 41 lakes across the state of Mississippi. To scale the influence of LULC classes on DOM distribution, we have classified 41 lakes into five clusters based on DOM compositions determined by parallel factor analysis. Four major DOM compositions including terrestrial humic-like (C1), microbial humic-like (C2), soil-derived humic-like (C3), and tryptophan-like or tyrosine like (C4) components were identified. Higher amounts of terrestrial humic-like and soil-derived humic-like DOM compositions were observed in lakes within watersheds dominated by forested, barren, wetlands, or agricultural areas with exposed unconsolidated soil. Higher amounts of microbial humic-like composition were observed in lakes surrounded by hay/pasture, rangeland, and urbanized areas. Additionally, protein-like DOM and ammonia were more enriched in larger lakes, indicating the influences of photochemical reactions. High amounts of forested areas and higher concentrations of terrestrial humic-like DOM composition were identified in all lakes suggesting forested areas in the watershed as the principal source of DOM in Mississippi lakes.
Research Document

Linking Cultural, Biological and Economic Values into Wetland Programs: Mississippi Band of Choctaw Indians' Pearl River Wetland Demonstration Project
This project aims to develop procedures for more reliably regenerating rivercane and for planting potential restoration sites in the Coastal Plain, and for maintenance of stands for cultural use by native peoples. We are assessing ecological factors associated with the establishment and maintenance of rivercane stands, developing methods for vegetative propagation of rivercane from rhizome segments, and attempting to transfer our findings directly to the Choctaw and other American Indian groups through local and regional symposia, workshops, and field days.
Email Contact

Mapping of Invasive Phragmites (Common Reed) in Gulf of Mexico Coastal Wetlands Using Multispectral Imagery and Unmanned Aerial Systems
In coastal wetlands of the Gulf of Mexico, the invasive plant species Phragmites australis (common reed) rapidly alters the ecology of a site by shifting plant communities from heterogeneous mixtures of plant species to homogenous stands of Phragmites. Phragmites grows in very dense stands at an average height of 4.6 m and outcompetes native plants for resources. To restore affected wetlands, resource managers require an accurate map of Phragmites locations. Previous studies have used satellite and manned aircraft-based remote-sensing images to map Phragmites in relatively large areas at a coarse scale; however, low-altitude high-spatial-resolution pixel-based classification approaches would improve the mapping accuracy. This study explores the supervised classification methods to accurately map Phragmites in the coastal wetlands at the delta of the Pearl River in Louisiana and Mississippi, USA, using high-resolution (8 cm ground sample distance; GSD) multispectral imagery collected from a small unmanned aerial system platform at an altitude of 120 m. We create a map through pixel-based Support Vector Machines (SVM) classification using blue, green, red, red edge, and near-infrared spectral bands along with a digital surface model (DSM), vegetation indices, and morphological attribute profiles (MAPs) as features. This study also demonstrates the effects of different features and their usefulness in generating an accurate map of Phragmites locations. Accuracy assessment based on a) a subset of training/testing samples (to show classifier performance) and b) the entire ground reference (GR) map (to show the quality of mapping) is demonstrated. Kappa, overall accuracy (OA), class accuracies, and their confidence intervals (CIs) are reported. An OA of 91% and kappa of 63 is achieved. The results of this study indicate that features such as MAPs are very useful in accurately mapping invasive Phragmites compared with existing region-based approaches.
Abstract and Document

Micromechanics of Undrained Response of Dilative Granular Media Using a Coupled DEM-LBM Model: A Case of Biaxial Test
In this paper, the Discrete Element Method (DEM) is coupled with the Lattice-Boltzmann Method (LBM) to model the undrained condition of dense granular media that display significant dilations under highly confined loading. DEM-only models are commonly used to simulate the micromechanics of an undrained specimen by applying displacements at the domain boundaries so that the specimen volume remains constant. While this approach works well for uniform strain conditions found in laboratory tests, it does not realistically represent non-uniform strain conditions that exist in the majority of real geotechnical problems. The LBM offers a more realistic approach to simulate the undrained condition since the fluid can locally conserve the system volume. To investigate the ability of the DEM-LBM model to effectively represent the undrained constraint while conserving volume and accurately calculating the stress path of the system, a two-dimensional biaxial test is simulated using the coupled DEM-LBM model, and the results are compared with those attained from a DEM-only constant volume simulation
Abstract Document

Nitrogen and Organic Carbon Contents of Agricultural Drainage Ditches of the Lower Mississippi Alluvial Valley
Use of agricultural fertilizers as a means of increasing production has resulted in excessive nutrient loading to agricultural drainage ditches, contributing to the Gulf of Mexico hypoxic zone. Drainage ditches can have wetland characteristics and functionality, including the capacity to remediate nutrient loading, which can be promoted using management practices. The purpose of this study was to assess relationships between organic carbon (C) and nitrogen (N) contents of drainage ditch sediment and waters and to evaluate the spatial scope in which organic C is potentially limiting N removal in drainage ditches throughout the Lower Mississippi Alluvial Valley (LMAV).

Nitrogen Management for Corn and Cotton in Mississippi Utilizing Advanced Technologies to Solve Spatial and Random Variances
The use of nitrogen based fertilizers to optimize plant growth is an essential component of modern crop production and has contributed to the astounding increase in yield produced by the American farming sector. Current nitrogen rate recommendations are based on a variety of environmental factors in specific regions and fertilizer is normally applied at a single rate to an entire crop production area. The objectives of this research are to: 1) understand spatial variation in crop growth and yield and their relationship to physical and fertility properties of soil; and 2) use ground- based reflectance sensors, coupled with in-season plant measurements to predict nitrogen levels in target crops in an effort to develop nitrogen management zones to guide variable rate, site specific nitrogen applications that optimize nitrogen utilization and efficiency. The use of variable-rate could decrease total amount of nitrogen being applied in crop production and more efficiently promote plant growth and development across an entire growing area.
Email Contact

Nutrient and Sediment Runoff from Agricultural Landscapes with Varying Suites of Conservation Practices in the Mississippi Alluvial Valley
Increasing concern regarding environmental degradation in coastal areas that experience annual hypoxic zones has led to the need for mitigation of nutrient laden runoff from inland landscapes. An annual occurrence of a hypoxic zone in the Gulf of Mexico has led to the development and implementation of nutrient reduction strategies throughout the Mississippi River Basin (MRB). With federal, state, and private financial and technical assistance, landowners have implemented best management practices (BMPs) to combat nutrient and sediment nonpoint source pollution; however, the effectiveness of these BMPs alone or utilized together has not been quantified. This study uses a field-scale, paired watershed approach in two watersheds in the Mississippi Alluvial Valley to test for differences in sediment and nutrient runoff concentrations between four management systems.
Abstract and publication site

Pollution assessment and land use land cover influence on trace metal distribution in sediments from five aquatic systems in southern USA
Trace elements and heavy metals concentrate in aquatic sediments, potentially endangering benthic organisms. Comparing the concentration of metals in different aquatic bodies will help evaluate their accumulation and distribution characteristics within these systems. Metal pollution and enrichment indices in sediments from diverse aquatic systems in Southern USA, including agricultural ponds, man-made reservoir, river, swamp, and coastal environment were investigated. Following total digestion of the sediments, the concentrations of chromium (Cr), cobalt (Co), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), cadmium (Cd), antimony (Sb), lead (Pb), and uranium (U) were measured using inductively coupled plasma-mass spectrometry (ICP-MS). Pb was found to be highly enriched in the sediment samples from all five environments. The samples from coastal and agricultural ponds showed highest degree of anthropogenic modification (enrichment factor
Research Document

Post-Logging Estimation of Loblolly Pine (Pinus Taeda) Stump Size, Area and Population Using Imagery from a Small Unmanned Aerial System
This study describes an unmanned aerial system (UAS) method for accurately estimating the number and diameters of harvested Loblolly Pine (Pinus taeda) stumps in a final harvest (often referred to as clear-cut) situation. The study methods are potentially useful in initial detection, quantification of area and volume estimation of legal or illegal logging events to help estimate the volumes and value of removed pine timber. The study sites used included three adjacent pine stands in East-Central Mississippi. Using image pattern recognition algorithms, results show a counting accuracy of 77.3% and RMSE of 4.3 cm for stump diameter estimation. The study also shows that the area can be accurately estimated from the UAS collected data. Our experimental study shows that the proposed UAS survey method has the potential for wide use as a monitoring or investigation tool in the forestry and land management industries.
Post-Logging Estimation of Loblolly Using UAS Document

Potential for recycling of suspended solids and nutrients by irrigation of tailwater from tailwater recovery systems
Within the Lower Mississippi Alluvial Valley, conservation practices are being utilized to mitigate nutrient loading to streams from agricultural landscapes. This study was conducted to determine the potential to use solids, phosphorus (P) and nitrogen (N) captured by tailwater recovery (TWR) systems for reuse onto production fields through irrigation applications.
Abstract and Document

Providing Accurate Data for Field Monitoring of Peanut Production
Reliable yield monitors have been developed for a variety of crops including corn, soybeans, wheat, and cotton. Due to the nature of harvesting and threshing peanuts, however, the ability to provide accurate yield data has been rudimentary, at best. The objective of this research is to use a system for yield measurement previously developed at Mississippi State University and commercialized through MSTX Agricultural Sensor Technologies (MAST), LLC to compare management zones, buy-point and field weights from adjusted and raw yield data in peanuts. The results of this study will potentially allow peanut producers to evaluate inputs, manage pests, make better land-use decisions and perform economic analysis in peanut production.
Email Contact

Quantifying Capture and Use of Tailwater Recovery Systems
The government has provided financial assistance on approximately 200 tailwater recovery systems in the state of Mississippi, and more in other states. The objective of this study was to quantify surface water capture and use within 31 tailwater recovery ditches (TWR) and on-farm storage reservoirs (OFS), so that conservation benefits could be evaluated. Water-level data were combined with system dimensions, rainfall data, and evaporation estimates to assess total gains and losses over the course of a year. Systems had a net positive balance of approximately 2,200,000 m3m3 (2,200 ML) of captured surface water. Losses from evaporation and infiltration were between 8.68 and 10.97
Abstract and Document

Quantifying Damage from Wild pigs with Small Unmanned Aerial Systems
Wild pig (Sus scrofa) population expansion and associated damage to crops, wildlife, and the environment is a growing concern in the United States. The destructive rooting behavior of wild pigs indicates where they have foraged and their general presence on the landscape. We used aerial imagery with a small unmanned aerial system to assess damage of corn (Zea mays) fields by wild pigs in the Mississippi Alluvial Valley of Mississippi, USA, during the 2016 growing season. Images were automatically classified using segmentation
Abstract and Document

Recent development of optical methods in rapid and non-destructive detection of aflatoxin and fungal contamination in agricultural products
The demand for developing rapid and non-destructive techniques that is suitable to real-time and on-line detection of aflatoxin and fungal contamination has received significant attentions. Measurement techniques based on fluorescence spectroscopy (FS), near-infrared spectroscopy (NIRS) and hyperspectral imaging (HSI) have provided interesting and promising results for detecting aflatoxin and/or fungal contamination in a variety of foods. As such, the main goal of this article is to give an overview of the current research progress of FS, NIRS and HSI techniques in rapid detection of aflatoxin and fungal contamination in different varieties of agricultural products.
Abstract and Document Site

Recent Developments and Applications of Hyperspectral Imaging for Rapid Detection of Mycotoxins and Mycotoxigenic Fungi in Food Products
Mycotoxins are the foremost naturally occurring contaminants of food products such as corn, peanuts, tree nuts, and wheat. As the secondary metabolites, mycotoxins are mainly synthesized by many species of the genera Aspergillus, Fusarium and Penicillium, and are considered highly toxic and carcinogenic to humans and animals. Most mycotoxins are detected and quantified by analytical chemistry-based methods. While mycotoxigenic fungi are usually identified and quantified by biological methods. However, these methods are time-consuming, laborious, costly, and inconsistent because of the variability of the grain-sampling process. It is desirable to develop rapid, non-destructive and efficient methods that objectively measure and evaluate mycotoxins and mycotoxigenic fungi in food. In recent years, some spectroscopy-based technologies such as hyperspectral imaging (HSI), Raman spectroscopy, and Fourier transform infrared spectroscopy have been extensively investigated for their potential use as tools for the detection, classification, and sorting of mycotoxins and toxigenic fungal contaminants in food. HSI integrates both spatial and spectral information for every pixel in an image, making it suitable for rapid detection of large quantities of samples and more heterogeneous samples and for in-line sorting in the food industry. In order to track the latest research developments in HSI, this paper gives a brief overview of the theories and fundamentals behind the technology and discusses its applications in the field of rapid detection and sorting of mycotoxins and toxigenic fungi in food products. Additionally, advantages and disadvantages of HSI are compared, and its potential use in commercial applications is reported.

Reduction of solids and nutrient loss from agricultural land by tailwater recovery systems
Best management practices are being implemented throughout the Lower Mississippi River Alluvial Valley with the aim of alleviating pressures placed on downstream aquatic systems by sediment and nutrient losses from agricultural land; however, research evaluating the performance of tail-water recovery (TWR) systems, an increasingly important practice, is limited. This study evaluated the ability of TWR systems to retain sediment and nutrients draining from agricultural landscapes.

Remote Sensing of Wildfire Using SUAS: Post-fire Mapping, Vegetation Recovery and Damage Analysis in Grand Bay National Estuarine Research Reserve, Mississippi. Drones
Wildfires can be beneficial for native vegetation. However, wildfires can impact property values, human safety, and ecosystem function. Resource managers require safe, easy to use, timely, and cost-effective methods for quantifying wildfire damage and regeneration. In this work, we demonstrate an approach using an unmanned aerial system (UAS) equipped with a MicaSense RedEdge multispectral sensor to classify and estimate wildfire damage in a coastal marsh. We collected approximately 7.2 km2 of five-band multispectral imagery after a wildfire event in February 2016, which was used to create a photogrammetry-based digital surface model (DSM) and orthomosaic for object-based classification analysis. Airborne light detection and ranging data were used to validate the accuracy of the DSM. Four-band airborne imagery from pre- and post-fire were used to estimate pre-fire health, post-fire damage, and track the vegetation recovery process. Immediate and long-term post-fire classifications, area, and volume of burned regions were produced to track the revegetation progress. The UAS-based classification produced from normalized difference vegetation index and DSM was compared to the Landsat-based Burned Area Reflectance Classification. Experimental results show the potential of using UAS and the presented approach compared to satellite-based mapping in terms of classification accuracies, turnaround time, and spatial and temporal resolutions.
Abstract Drones Open Access Journal

Representation of Solid and Nutrient Concentrations in Irrigation Water from Tailwater-Recovery Systems by Surface Water Grab Samples
Tailwater recovery (TWR) systems are being implemented on agricultural landscapes to create an additional source of irrigation water. Existing studies have sampled TWR systems using grab samples; however, the representation of solids and nutrient concentrations in these samples to water being irrigated from TWR systems has yet to be investigated. In order to test whether grab samples are representative of water pumped from TWR systems for irrigation use, this study compared concentrations of total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NO−3NO−2NO3−NO2−), and ammonium (NH 4NH4 ). Grab samples were collected simultaneously from the surface water and from the respective outflow of irrigation infrastructure in six TWR systems. Comparison of 14 irrigation events showed TSS, TP, TN, TKN, NO−3NO−2NO3−NO2−, and NH 4NH4 did not differ (Pillai’s trace5,1=0.307trace5,1=0.307, p>0.5p>0.5) between surface water grab samples and irrigation water samples. No differences (p>0.05p>0.05) were found for TN, TP, NH 4NH4 , and TKN across sites. This research suggests surface water grab samples from TWR systems represent the solid and nutrient concentrations being irrigated at that moment of time.
Tailwater-Recovery Systems ...Grab Samples

Research on the Performance of Tail-Water Recovery Systems to Alleviate Downstream Aquatic Systems
Best management practices are being implemented throughout the Lower Mississippi River Alluvial Valley with the aim of alleviating pressures placed on downstream aquatic systems by sediment and nutrient losses from agricultural land; however, research evaluating the performance of tail-water recovery (TWR) systems, an increasingly important practice, is limited. This study evaluated the ability of TWR systems to retain sediment and nutrients draining from agricultural landscapes.

Research to Support Integrated Management Systems of Aquatic and Terrestrial Invasive Species and Bioinformatics
GRI is coordinating a multidisciplinary, multi-year research and outreach project with the U.S. Geological Survey Invasive Species Program and the National Biological Information Infrastructure to develop research and biological information products on aquatic and terrestrial invasive species, centered in the MidSouth region. We are developing directed, peer-reviewed research and informatics tools to enhance the management of invasive species: aquatic invasive plants, developing an integrated National Early Detection and Rapid Response Web site, research on the renegade biological control agent, cactus moth (Cactoblastis cactorum), continued support of the Invasive Plant Atlas of the Mid-South (IPAMS), and the development of biological informatics resources in the areas of invasive species and pollinators.

Screening Mississippi River Levees Using Texture-based and Polarimetric-based Features from Synthetic Aperture Radar Data
This article reviews the use of synthetic aperture radar remote sensing data for earthen levee mapping with emphasis on finding the slump slides on the levees. Earthen levees built on the natural levees parallel to the river channel are designed to protect large areas of populated and cultivated land in the Unites States from flooding. One of the signs of potential impending levee failure is the appearance of slump slides. On-site inspection of levees is expensive and time-consuming, therefore, a need to develop efficient techniques based on remote sensing technologies is mandatory to prevent failures under flood loading. Analysis of multi-polarized radar data is one of the viable tools for detecting the problem areas on the levees. In this study, we develop methods to detect anomalies on the levee, such as slump slides and give levee managers new tools to prioritize their tasks. This paper presents results of applying the NASA JPL
Abstract Document

Sequential Applications of Diquat to Control Flowering Rush (Butomus Umbellatus L.) in Mesocosms. Journal of Aquatic Plant Management
Flowering rush (Butomus umbellatus L.) is an aggressive, invasive, aquatic plant spreading throughout water bodies in the northern United States and southern Canada, displacing many native aquatic/wetland plants. This can disrupt ecosystem processes and affect human uses of water bodies. Operational management in Detroit Lakes, MN, reduced flowering rush biomass and propagules by >80% using two sequential, submersed applications of diquat (0.37 mg L-1 ) per growing season (4 wk apart). However, in dense colonies, long-term control has taken years to achieve, suggesting a more aggressive treatment regime may be necessary. A mesocosm study was initiated in 2015 and repeated in 2016 to further investigate diquat (0.37 mg L-1 ; 12 h exposure time) efficacy using one to four biweekly (every other week) sequential herbicide applications to improve flowering rush control.
Abstract Journal of Plant and Aquatic Management,

Simulated mechanical control of flowering rush (Butomus umbellatus) under mesocosm conditions
lowering rush (Butomus umbellatus L.) is an invasive aquatic and wetland plant capable of developing monotypic stands in emergent and submersed sites. This plant can rapidly outcompete native vegetation and impede human practices by reducing recreation (boating, fishing, and skiing) and disrupting agricultural use of water resources (irrigation canals). Mechanical removal practices occurring biweekly, monthly, bimonthly, and once per growing season were compared with chemical control with diquat applied sequentially at 0.19 ppmv ai for two consecutive months over 2 yr (2016 and 2017). Biweekly removal gave the most consistent control of B. umbellatus biomass and propagules. Diquat application along with monthly and bimonthly clippings gave varying degrees of B. umbellatus control. Clipping once per growing season did not control B. umbellatus when compared with reference plants, while clipping B. umbellatus every 2 wk (biweekly) controlled rush propagules most effectively. However, it is unlikely this method will be sufficient as a stand-alone control option due to the slow speed of harvester boats, the potential these boats have to spread B. umbellatus propagules to more sites, and the expense of mechanical operations. However, clipping could be used as part of an integrated strategy for B. umbellatus control.
Abstract Cambridge: Invasive Plant Science Management

Site Specific Technologies
GRI's New Satellite and Computer-Based Technology for Agriculture (NSCTA) project is to investigate site-specific technologies as they pertain to natural resource management, precision farming, agribusiness, and decision making in agriculture. The project develops research activities in an effort to produce new knowledge concerning applications of these technologies in Mississippi and the nation.
Email Contact

Southern P Indices, Water Quality Data, and Modeling (APEX, APLE, and TBET) Results: A Comparison
Phosphorus (P) Indices in the southern United States frequently produce different recommendations for similar conditions. We compared risk ratings from 12 southern states (Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, and Texas) using data collected from benchmark sites in the South (Arkansas, Georgia, Mississippi, North Carolina, Oklahoma, and Texas). Phosphorus Index ratings were developed using both measured erosion losses from each benchmark site and Revised Universal Soil Loss Equation 2 predictions; mostly, there was no difference in P Index outcome. The derived loss ratings were then compared with measured P loads at the benchmark sites by using equivalent USDA–NRCS P Index ratings and three water quality models (Annual P Loss Estimator [APLE], Agricultural Policy Environmental eXtender [APEX], and Texas Best Management Practice Evaluation Tool [TBET]). Phosphorus indices were finally compared against each other using USDA–NRCS loss ratings model estimate correspondence with USDA–NRCS loss ratings. Correspondence was 61% for APEX, 48% for APLE, and 52% for TBET, with overall P index correspondence at 55%. Additive P Indices (Alabama and Texas) had the lowest USDA–NRCS loss rating correspondence (31%), while the multiplicative (Arkansas, Florida, Louisiana, Mississippi, South Carolina, and Tennessee) and component (Georgia, Kentucky, and North Carolina) indices had similar USDA–NRCS loss rating correspondence—60 and 64%, respectively. Analysis using Kendall’s modified Tau suggested that correlations between measured and calculated P-loss ratings were similar or better for most P Indices than the models.
Document Document Site

Spatial and spectral Hyperspectral Classification Using Local Binary Patterns and Markov Random Fields
Local binary patterns (LBPs) have been extensively used to yield spatial features for the classification of general imagery, and a few recent works have applied these patterns to the classification of hyperspectral imagery. Although the conventional LBP formulation employs only the signs of differences between a central pixel and its surrounding neighbors, it has been recently demonstrated that the difference magnitudes also possess discriminative information. Consequently, a sign-and-magnitude LBP is proposed to provide a spatial
Abstract Document Site

Spatial Detection of Agri-terrorism
This GRI project develops and deploys an automated target recognition system that utilizes hyperspectral imagery to detect biological or chemical contamination of vegetation. The Automated Target Recognition - ATR - system is applied to the problem of BioSecurity, i.e. the detection of crop contamination via biological or chemical agents.
Email Contact

Spatial Variation and Temporal Trend of Water Quality
NGI conducted ground truth observations and standardize algorithms to produce and evaluate the spatial and temporal variations of water quality parameters in the Northern Gulf of Mexico (NGOM). The effort is aimed at improving the monitoring of the NGOM ecosystem based on remote sensing and understanding the dynamics of harmful algae blooms in the region.
Email Contact

Spectral-Based Screening Approach Evaluating Two Specific Maize Lines With Divergent Resistance to Invasion by Aflatoxigenic Fungi
In an effort to control aflatoxin contamination in food and/or feed grains, a segment of research has focused on host resistance to eliminate aflatoxin from susceptible crops, including maize. To this end, screening tools are key to identifying resistant maize genotypes. The traditional field screening techniques, the kernel screening laboratory assay (KSA), and analytical methods (e.g., ELISA) used for evaluating corn lines for resistance to fungal invasion, all ultimately require sample destruction. A technological advancement on the basic BGYF presumptive screening test, fluorescence hyperspectral imaging offers an option for non-destructive and rapid image-based screening. The present study aimed to differentiate fluorescence spectral signatures of representative resistant and susceptible corn hybrids infected by a toxigenic (SRRC-AF13) and an atoxigenic (SRRC-AF36) strain of Aspergillus flavus, at several time points (5, 7, 10, and 14 days), in order to evaluate fluorescence hyperspectral imaging as a viable technique for early, non-invasive aflatoxin screening in resistant and susceptible corn lines. The study utilized the KSA to promote fungal growth and aflatoxin production in corn kernels inoculated under laboratory conditions and to provide actual aflatoxin values to relate with the imaging data. Each time point consisted of 78 kernels divided into four groups (30-susceptible, 30-resistant, 9-susceptible control, and 9-resistant control), per inoculum. On specified days, kernels were removed from the incubator and dried at 60
Research Document

Structure from Motion with UAVs: A Best Practice Guide for Users
Tips and tricks to help you get started using low-cost unmanned aerial vehicles to generate accurate three-dimensional models for stream channels and drainage ditches.
Photo of Cover Document

Temporal Effects on Internal Fluorescence Emissions Associated with Aflatoxin Contamination from Corn Kernel Cross-sections Inoculated with Toxigenic and Atoxigenic Aspergillus Flavus
Non-invasive, easy to use and cost-effective technology offers a valuable alternative for rapid detection of carcinogenic fungal metabolites, namely aflatoxins, in commodities. One relatively recent development in this area is the use of spectral technology. Fluorescence hyperspectral imaging, in particular, offers a potential rapid and non-invasive method for detecting the presence of aflatoxins in maize infected with the toxigenic fungus Aspergillus flavus. Earlier studies have shown that whole maize kernels contaminated with aflatoxins exhibit different spectral signatures from uncontaminated kernels based on the external fluorescence emission of the whole kernels. Here, the effect of time on the internal fluorescence spectral emissions from cross-sections of kernels infected with toxigenic and atoxigenic A. flavus, were examined in order to elucidate the interaction between the fluorescence signals emitted by some aflatoxin contaminated maize kernels and the fungal invasion resulting in the production of aflatoxins.

The Application of Structure from Motion Techniques in Late-season Corn Damage
Green snap occurs when corn stalks are broken in high wind. Late in the season, green snap produces yield losses that are immediate and irreversible. Losses are proportional to the percentage of plants lost, thus estimation of damage extent is important for calculating economic loss. Unmanned aerial vehicles are capable of creating a 3D-model, called a digital surface model, of the crop canopy using structure from motion techniques. The objective of this study was to compare image- versus structure-based calculations of damaged area. The structure-based calculations were more reflective of the field assessment. While the latter approach showed promise, more development of protocols is needed for reliability and operational success.
Abstract Precision Agriculture

The Use of Early Detection and Rapid Response Protocol for the Control of Waterlettuce
Waterlettuce was identified growing in a small area of an impoundment (Powe Pond) located in the Thad Cochran Research, Technology, and Economic Development Park, Starkville, MS. As a result of this, a study was conducted to eradicate the waterlettuce population in the pond and survey and eradicate any plants that had escaped into the outflow creek using aquatic labeled herbicides.

Torpedograss control via submersed applications of systemic and contact herbicides in mesocosms
Torpedograss control via submersed applications of systemic and contact herbicides in mesocosms
Research Gate

UAS with MicroSense RedEdge Payload Help Monitor and Manage Forest Resortation
Unmanned Aerial Systems (UAS) carry a multispectral senor that produce images that provides biologist and geographic information system specialists with changes in the woodlands and vegetation in almost real time. These systems also show the density and regrowth of woodland, marsh, and coastal areas. Mississippi State Universityâs Geosystems Research Institute is assisting the Grand Bay National Estuarine Research Reserve (GBNERR) and the U.S. Forestry Service with surveying the 4,200 acres that were burned during a large wildfire that reaches from southeast Jackson County into Alabama. These experts utilized the Altavian Nova Block III to inspect the area from 1,000 feet, and they deployed the MicaSense RedEdge. The MicaSense RedEdge has the ability to sense energy at five different wavelengths. Two of the five wavelengths exceed our vision in the Near Infrared Region (NIR) of the electromagnetic spectrum. The senor provides researchers with accurate data that projects the status of vegetation and stress of areas within the ecosystem. With this knowledge, researchers and specialists can aid in the revegetation of the burned woodlands and marsh of the GBNERR, the Grand Bay National Wildlife Refuge and neighboring lands.

UAS Research
GRI researchers are working to incorporate the use of unmanned aerial vehicles (UAVs) in site-specific agricultural research. MSU currently holds certificates of authorization from the Federal Aviation Administration to operate UAVs for research purposes only. The research looks at plant growth, nutrient management, irrigation and herbicide application.
Email Contact

Unmanned Aerial Systems
GRI scientists are researching the effective use of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USV's) commonly referred to as drones, in how they can be used safely to assess crops, evaluate woodlands, conduct wildlife surveys, gauge river flow and monitor the Gulf of Mexico environmental health and watershed, as well as helping NOAA increase the accuracy of severe weather forecasts. These unmanned aerial and surface/water systems use remote sensing, global positioning--and geographic information systems to collect and analyze sites specific data that farmers, foresters, wildlife rangers, oceanographers and marine scientists can use to create and apply effective prescriptions for every inch of an agricultural field, ocean, river, forest and wildlife management areas.

Use of Visible–Near-Infrared (Vis-NIR) Spectroscopy to Detect Aflatoxin B1 on Peanut Kernels
Current methods for detecting aflatoxin contamination of agricultural and food commodities are generally based on wet chemical analyses, which are time-consuming, destructive to test samples, and require skilled personnel to perform, making them impossible for large-scale nondestructive screening and on-site detection. In this study, we utilized visible–near-infrared (Vis-NIR) spectroscopy over the spectral range of 400–2500 nm to detect contamination of commercial, shelled peanut kernels (runner type) with the predominant aflatoxin B1 (AFB1). The artificially contaminated samples were prepared by dropping known amounts of aflatoxin standard dissolved in 50:50 (v/v) methanol/water onto peanut kernel surface to achieve different contamination levels. The partial least squares discriminant analysis (PLS-DA) models established using the full spectra over different ranges achieved good prediction results. The best overall accuracy of 88.57% and 92.86% were obtained using the full spectra when taking 20 and 100 parts per billion (ppb), respectively, as the classification threshold. The random frog (RF) algorithm was used to find the optimal characteristic wavelengths for identifying the surface AFB1-contamination of peanut kernels.
Abstract and Reearch

Using Unmanned Aerial Vehicles for High-Resolution Remote Sensing to Map Invasive Phragmites Australis in Coastal Wetlands
The wetland plant species, Phragmites australis, is present on every continent except Antarctica. Both native and non-native subspecies thrive in the USA with the non-natives quickly displacing native wetland plants. Along the Gulf Coast, Phragmites grows in very dense stands, and at heights of greater than 4.6 m, is usually the tallest grass species in a wetland, estuary, and marsh ecosystems. Phragmites is known to alter the ecology of these wetland systems making them less suitable as habitat for many species of flora and fauna. Furthermore, Phragmites presents a navigation hazard to smaller boats by impairing visibility along shorelines and around bends of canals and rivers. Management efforts targeting non-native Phragmites rely heavily on accurately mapping invaded areas. Historically, mapping has been done through walking the perimeter of a stand with a Global Positioning System (GPS) unit, using satellite imagery, or through the use of aerial photography from manned aircraft. These methods are time consuming, are expensive, can have an inadequate resolution, and in some cases are prone to human error. In this work, an Unmanned Aerial System (UAS) was used to capture visible imagery to create a basin-wide distribution map of a large wetland along the US Pearl River delta in southeastern Louisiana. The imagery was collected in the summer and individual images were mosaicked to create a larger map. We then evaluated the use of texture analysis on the mosaics to automatically map the invasive. Specifically, Gabor filters, grey level co-occurrence matrices, segmentation-based fractal texture analysis, and wavelet-based texture analysis were compared for mapping the Phragmites. Our experimental results, conducted using the imagery we collected over four study areas (approximately 2250 ha) along the US Pearl River delta, indicate the proposed texture-based approach yields an average accuracy of 85%, an average kappa accuracy of 70%. These maps have shown to be very useful for resource managers to hasten the eradication efforts of Phragmites.
Abstract and Document

Variation in Dissolved Organic Matter, Trace Metals, and Acidification Parameters in the Western Mississippi Sound
The total amount of oysters harvested in the Mississippi Sound has declined by 85.71% over the last 13 years. The objective of this study was to assess the influence of water quality on the oysters, specifically the temporal changes in dissolved organic matter (DOM), trace elements, and ocean acidification parameters over the largest oyster bed in the western Mississippi Sound.

WISDOM - Weather In-Situ Deployment Optimization Method
GRI scientists and students are participating in WISDOM, the Weather In-Situ Deployment Optimization Method research program that seeks to improve hurricane forecasting time by three to seven days before a storm's landfall by providing wind and atmospheric data in areas of the Atlantic basin that are poorly observed. The WISDOM program launches small super-pressure balloons with payloads that include GPS and satellite radio communications capabilities.
Email Contact

Geosystems Research Institute  •  Contact GRI
Modified: December 2, 2020  •  WebMaster  •  Intranet