Mustafa Mirik

Hyperspectral Spectrometry as a Means to Differentiate Uninfested and Infested Winter Wheat by Greenbug (Hemiptera: Aphididae)

Although spectral remote sensing techniques have been used to study many ecological variables and biotic and abiotic stresses to agricultural crops over decades, the potential use of these techniques for greenbug, Schizaphis graminum (Rondani) (Hemiptera: Aphididae) infestations and damage to wheat, Triticum aestivum L., under field conditions is unknown. Hence, this research was conducted to investigate: 1) the applicability and feasibility of using a portable narrow-banded (hyperspectral) remote sensing instrument to identify and discern differences in spectral reflection patterns (spectral signatures) of winter wheat canopies with and without greenbug damage; and 2) the relationship between miscellaneous spectral vegetation indices and greenbug density in wheat canopies growing in two fields and under greenhouse conditions. Both greenbug and reflectance data were collected from 0.25-, 0.37-, and 1-m2 plots in one of the fields, greenhouse, and the other field, respectively. Regardless of the growth conditions, greenbug-damaged wheat canopies had higher reflectance in the visible range and less in the near infrared regions of the spectrum when compared with undamaged canopies. In addition to percentage of reflectance comparison, a large number of spectral vegetation indices drawn from the literature were calculated and correlated with greenbug density. Linear regression analyses revealed high relationships (R2 ranged from 0.62 to 0.85) between greenbug density and spectral vegetation indices. These results indicate that hyperspectral remotely sensed data with an appropriate pixel size have the potential to portray greenbug density and discriminate its damage to wheat with repeated accuracy and precision.

Satellite remote sensing of wheat infected by Wheat streak mosaic virus.

The prevalence of wheat streak mosaic, caused by Wheat streak mosaic virus, was assessed using Landsat 5 Thematic Mapper (TM) images in two counties of the Texas Panhandle during the 2005-2006 and 2007-2008 crop years. In both crop years, wheat streak mosaic was widely distributed in the counties studied. Healthy and diseased wheat were separated on the images using the maximum likelihood classifier. The overall classification accuracies were between 89.47 and 99.07% for disease detection when compared to ground truth field observations. Omission errors (i.e., pixels incorrectly excluded from a particular class and assigned to other classes) varied between 0 and 12.50%. Commission errors (i.e., pixels incorrectly assigned to a particular class that actually belong to other classes) ranged from 0 to 23.81%. There were substantial differences between planted wheat acreage reported by the United States Department of Agriculture-National Agricultural Statistics Service (USDA-NASS) and that detected by image analyses. However, harvested wheat acreage reported by USDA-NASS and that detected by image classifications were closely matched. These results indicate that the TM image can be used to accurately detect and quantify incidence of wheat streak mosaic over large areas. This method appears to be one of the best currently available for identification and mapping disease incidence over large and remote areas by offering a repeatable, inexpensive, and synoptic strategy during the course of a growing season.

Structural biomass partitioning in regrowth and undisturbed mesquite (Prosopis glandulosa): implications for bioenergy uses

Honey mesquite (Prosopis glandulosa Torr.) which grows on grasslands and rangelands in southwestern USA may have potential as a bioenergy feedstock because of existing standing biomass and regrowth potential. However, regrowth mesquite physiognomy is highly different from undisturbed mesquite physiognomy and little is known regarding growth rates and structural biomass allocation in regrowth mesquite. We compared canopy architecture, aboveground biomass and relative allocation of biomass components in regrowth (RG) trees of different known ages with undisturbed (UD) trees of similar canopy height to each RG age class. RG trees in most age classes (2–12 years old) had greater canopy area, leaf area, basal stem number, twig (<0.5u2003cm diameter) mass and small stem (0.5–3u2003cm diameter) mass than UD trees of the same height. Large stem (>3u2003cm diameter) mass was similar between RG and UD trees in all height classes. Ages of UD trees were determined after harvest and further comparisons were made between age, canopy structure and biomass in RG and UD trees. Relationships between age and total mass, age and height, and age and canopy area indicated a faster growth rate in RG than in UD trees. Large stem mass as a percentage of total tree mass accumulated more rapidly with age in RG than UD trees. Leaf area index and leafu2003:u2003twig mass ratio were maintained near 1 in all RG and UD trees. Regrowth potential may be one of the most important features of mesquite in consideration as a bioenergy feedstock.

Spectral vegetation indices selected for quantifying Russian wheat aphid ( Diuraphis noxia ) feeding damage in wheat ( Triticum aestivum L.)

The effects of insect infestation in agricultural crops are of major economic interest because of increased cost of pest control and reduced final yield. The Russian wheat aphid (RWA: Diuraphis noxia) feeding damage (RWAFD), referred to as “hot spots”, can be traced, indentified, and isolated from uninfested areas for site specific RWA control using remote sensing techniques. Our objectives were to (1) examine the use of spectral reflectance characteristics and changes in selected spectral vegetation indices to discern infested and uninfested wheat (Triticum aestivum L.) by RWA and (2) quantify the relationship between spectral vegetation indices and RWAFD. The RWA infestations were investigated in irrigated, dryland, and greenhouse growing wheat and spectral reflectance was measured using a field radiometer with nine discrete spectral channels. Paired t test comparisons of percent reflectance made for RWA-infested and uninfested wheat yielded significant differences in the visible and near infrared parts of the spectrum. Values of selected indices were significantly reduced due to RWAFD compared to uninfested wheat. Simple linear regression analyses showed that there were robust relationships between RWAFD and spectral vegetation indices with coefficients of determination (r2) ranging from 0.62 to 0.90 for irrigated wheat, from 0.50 to 0.87 for dryland wheat, and from 0.84 to 0.87 for the greenhouse experiment. These results indicate that remotely sensed data have high potential to identify and separate “hot spots” from uninfested areas for site specific RWA control.

Comparison of Ground-Measured and Image-Classified Mesquite (Prosopis glandulosa) Canopy Cover

Abstract Remote sensing has long been recognized as a rapid, inexpensive, nondestructive, and synoptic technique to study rangeland vegetation and soils. With respect to the worldwide phenomenon of woody plant invasion on many grasslands and rangelands, there is increasing interest in accurate and cost-effective quantification of woody plant cover and distribution over large land areas. Our objectives were to 1) investigate the relationship between ground-measured and image-classified honey mesquite (Prosopis glandulosa Torr.) canopy cover at three sites in north Texas using high spatial resolution (0.67-m) aerial images, and 2) examine the suitability of aerial images with different spatial resolutions (0.67-m, 1-m, and 2-m) for accurate estimation of mesquite canopy cover. The line intercept method and supervised maximum likelihood classifier were used to measure mesquite cover on the ground and on images, respectively. Images all were taken in September when mesquite foliage was photosynthetically active and most herbaceous vegetation was dormant. The results indicated that there were robust agreements between classified and ground-measured mesquite cover at all three sites with the coefficients of determination (r2) ≥u200a0.95. Accuracy of lower spatial resolution images ranged from r2u200au200a=u200au200a0.89–0.93, with the 2-m spatial resolution image on one of the sites at r2u200au200a=u200au200a0.89. For all sites, the overall, producers, and users accuracies, and kappa statistics were 92% and 97%, 91% and 99%, 85% and 96%, and 0.82 and 0.95 for 2-m and 0.67-m spatial resolution images, respectively. Results showed that images at all three spatial resolution levels were effective for estimating mesquite cover over large and remote or inaccessible areas.

Utility of Satellite and Aerial Images for Quantification of Canopy Cover and Infilling Rates of the Invasive Woody Species Honey Mesquite (Prosopis Glandulosa) on Rangeland

Woody plant encroachment into grasslands and rangelands is a world-wide phenomenon but detailed descriptions of changes in geographical distribution and infilling rates have not been well documented at large land scales. Remote sensing with either aerial or satellite images may provide a rapid means for accomplishing this task. Our objective was to compare the accuracy and utility of two types of images with contrasting spatial resolutions (1-m aerial and 30-m satellite) for classifying woody and herbaceous canopy cover and determining woody infilling rates in a large area of rangeland (800 km2) in north Texas that has been invaded by honey mesquite (Prosopis glandulosa). Accuracy assessment revealed that the overall accuracies for the classification of four land cover types (mesquite, grass, bare ground and other) were 94 and 87% with kappa coefficients of 0.89 and 0.77 for the 1-m and 30-m images, respectively. Over the entire area, the 30-m image over-estimated mesquite canopy cover by 9 percentage units (10 vs. 19%) and underestimated grass canopy cover by the same amount when compared to the 1-m image. The 30-m resolution image typically overestimated mesquite canopy cover within 225 4-ha sub-cells that contained a range of mesquite covers (1–70%) when compared to the 1-m image classification and was not suitable for quantifying infilling rates of this native invasive species. Documenting woody and non-woody canopy cover on large land areas is important for developing integrated, regional-scale management strategies for rangeland and grassland regions that have been invaded by woody plants.

High spectral and spatial resolution hyperspectral imagery for quantifying Russian wheat aphid infestation in wheat using the constrained energy minimization classifier

Abstract. The effects of insect infestation in agricultural crops are of major ecological and economic interest because of reduced yield, increased cost of pest control and increased risk of environmental contamination from insecticide application. The Russian wheat aphid (RWA, Diuraphis noxia) is an insect pest that causes damage to wheat (Triticum aestivum L.). We proposed that concentrated RWA feeding areas, referred to as “hot spots,” could be identified and isolated from uninfested areas within a field for site specific aphid management using remotely sensed data. Our objectives were to (1) investigate the reflectance characteristics of infested and uninfested wheat by RWA and (2) evaluate utility of airborne hyperspectral imagery with 1-m spatial resolution for detecting, quantifying, and mapping RWA infested areas in commercial winter wheat fields using the constrained energy minimization classifier. Percent surface reflectance from uninfested wheat was lower in the visible and higher in the near infrared portions of the spectrum when compared with RWA-infested wheat. The overall classification accuracies of > 89 % for damage detection were achieved. These results indicate that hyperspectral imagery can be effectively used for accurate detection and quantification of RWA infestation in wheat for site-specific aphid management.

Delivered Biomass Costs of Honey Mesquite (Prosopis glandulosa) for Bioenergy Uses in the South Central USA

Honey mesquite (Prosopis glandulosa Torr.), a multistemmed tree that grows on grasslands and rangelands in the South Central USA (Texas, Oklahoma, and New Mexico), may have potential as a bioenergy feedstock due to a large amount of existing standing biomass and significant regrowth potential following initial harvest. The objective of this research was to determine the cost to harvest, store, and deliver mesquite biomass feedstock to a bioelectricity plant under the assumption that the rights to harvest mesquite could be acquired in long-term leases. The advantage of mesquite and similar rangeland shrubs as bioenergy feedstocks is that they do not grow on land better suited for growing food or fiber and thus will not impact agricultural food markets as corn grain ethanol has done. In addition, there are no cultivation costs. Results indicated that mesquite biomass density (Mgxa0ha−1) and harvesting costs are major factors affecting cost of delivered biomass. Annual biomass consumption by the bioelectricity plant and percent of the total system area that contains biomass density that is suitable for harvest significantly affected land- related factors including total system area needed per bioelectricity plant and transport costs. Simulation results based on actual biomass density in Texas showed that higher and more spatially consistent biomass density would be an important factor in selecting a potential location for the bioelectricity plant. Harvesting mesquite has the potential for bioenergy feedstock given certain densities and total land areas since higher harvest and transport costs are offset by essentially no production costs.

Woody cover and grass production in a mesquite savanna: geospatial relationships and precipitation.

Abstract Woody plant effects on grass production at specific points in some rangeland savannas may be a function of numerous surrounding woody plants with lateral roots that extend into those patches of grass. This study determined the effects of increasing zones of honey mesquite (Prosopis glandulosa Torr.) influence on the production of three perennial grass types (C4 shortgrasses, C3 midgrasses, and C4 midgrasses) at specific points in gaps between mesquite trees in each of five years. Mesquite canopy cover was determined by geospatial analysis of aerial images for progressively increasing zones (0–5, 0–10, 0–15, and 0–20 m radius) surrounding each grass production point. The woody cover/grass production relationships were mostly linear for C4 shortgrasses and C3 midgrasses, and mostly a declining exponential curve for C4 midgrasses in all canopy zones, indicating that C4 midgrasses were most sensitive to increasing mesquite cover, especially at covers >30%. The relationship between mesquite cover and C4 shortgrass production was strongest (i.e., highest r2) when the smallest woody cover zones (0–5 and 0–10 m) were included. In contrast, the relationship between cover and C4 midgrass production was strongest when the largest zones (0–15 and 0–20 m) were included. These differences were attributed to an inability of C4 midgrasses to persist in smaller intercanopy gaps resulting from increases in mesquite density and infilling. Annual precipitation and C3 annual grass invasions played a large role in determining the woody cover/grass production relationship for each grass type. This study illustrates the complexity involved in quantifying woody cover/grass production relationships in savanna ecosystems. Maintaining productive stands of C4 midgrasses may be facilitated by maintaining woody cover below 30% threshold levels and possibly by limiting grazing during episodic high rainfall events in midsummer when this grass type becomes somewhat decoupled from woody cover effects.

Canopy Area and Aboveground Mass of Individual Redberry Juniper (Juniperus pinchotii) Trees

Abstract There is increasing interest in using canopy area to quantify biomass of invasive woody plants on large land areas of rangelands for a variety of reasons. For those woody species that emphasize lateral canopy growth over vertical growth it may be possible to relate canopy area to aboveground mass (AGM). Our objective was to determine the utility of external canopy measurements (area, volume, and height) for predicting AGM and the percentage of AGM that is wood (PW; i.e., stems >u200a3 cm diameter) in individual redberry juniper (Juniperus pinchotii Sudw.) plants in west Texas. The canopy area to height relationship was curvilinear and indicated that at heights >u200a3 m, there was more lateral (canopy area) than vertical canopy growth. We found a strong linear relationship between canopy area and AGM (r2u200au200a=u200au200a0.94; AGM range 9 kg to 688 kg) and it appeared that AGM could be predicted in individual trees from canopy area. Moreover, the canopy area/AGM relationship developed from smaller trees was able to adequately predict AGM of larger trees. Height was a less effective predictor of AGM (r2u200au200a=u200au200a0.66), and incorporation of height with canopy area to determine canopy volume did little to improve accuracy of estimating AGM over canopy area alone. The canopy area/PW relationship was curvilinear (the rate of increase in PW declined in larger trees) and PW reached 60–70% in the largest trees.