Ahmad Khalilian

ASSESSING NITROGEN CONTENT OF GOLF COURSE TURFGRASS CLIPPINGS USING SPECTRAL REFLECTANCE

Feasibility of a practical indoor reflectance-based sensor was studied to assess nitrogen content of turfgrass clippings from spectral reflectance data. Turfgrass clipping samples were obtained from commercial golf course putting greens, and their reflectance were measured using a dual-type spectroradiometer under artificial illumination 3 h and 51 h after mowing. The reflectance values in green band (520 to 580 nm) and the NIR band (770 to 1050 nm) increased as the nitrogen content increased. Four wavelength bands at 550, 680, 770, and 810 nm were selected to develop and compare several regression models with varying number of variables. All models performed well (R2 > 0.82) and predicted the nitrogen content with reasonable standard error of prediction (SEP) values (SEP < 0.62%) for the data taken 3 h after mowing. However, the data taken 51 h after mowing on the same samples did not yield good results (R2 1.04%). A discriminant analysis showed that the regression model with two wavelength variables performed as well as the models with a higher number of variables. A simple reflectance sensor using even only one photodiode and bandpass filter can be developed to predict or classify the nitrogen content of turfgrass clippings when the reflectance data are taken within several hours of mowing.

VARIABLE DEPTH TILLAGE BASED ON GEO-REFERENCED SOIL COMPACTION DATA IN COASTAL PLAIN REGION OF SOUTH CAROLINA

This study deals with determining the optimum tillage depth from geo-referenced soil compaction and soil electrical conductivity data. Soil compaction data was analyzed and mapped. Based on the measurements, 75% of the test field required shallower tillage depth than recommended tillage depth for coastal plain soils. Variable depth tillage, no-tillage and conventional tillage systems were compared and the relationships between tillage depth, soil electrical conductivity, crop responses, and yield were investigated in cotton production. The results showed that the main factor in yield was soil texture. Also, the energy savings of 15.82 kW.h (42.8%) and fuel saving of 4.58 L (28.4%) could be achieved by adoption of variable-depth tillage as compared to uniform-depth tillage.

AN ALGORITHM TO DETERMINE THE OPTIMUM TILLAGE DEPTH FROM SOIL PENETROMETER DATA IN COASTAL PLAIN SOILS

Soil compaction is a significant problem in the southeastern Coastal Plain soils. Cone penetrometers are used widely for soil strength measurement and tillage decisions. However, there is no standard or comprehensive method for determining the optimum tillage depth from soil penetrometer data in Coastal Plain soils. Our objective was to develop an algorithm for determining the optimum tillage depth from soil cone penetrometer measurements to effectively remove the hardpan. Intensive geo-referenced soil cone penetrometer measurements were obtained and each cone index profile was graphically examined. The results showed six main patterns for penetrometer profiles in a Dothan loamy sand soil. An algorithm and computer program was developed to determine the optimum tillage depth from the penetrometer data taken in a two-year study (2000 and 2001). The results clearly indicated that the thickness and the location of the hardpan can be determined from the soil cone penetrometer data. A great amount of variation was observed in the depth and the thickness of the hardpan (4 to 25 cm) as well as in the optimum tillage depth (25 to 45 cm) in both years.

Injected and Broadcast Application of Composted Municipal Solid Waste in Cotton

Equipment was developed and tested for injection and broadcast application of municipal solid waste (MSW) compost at selected rates to agricultural land for cotton production. Replicated tests were conducted to determine the effects of injected versus broadcast applied compost on soil parameters (organic matter, soil compaction, and soil fertility) and plant growth. All broadcast application rates of compost significantly reduced hardpan formation in the top 15 cm of soil compared to no compost application. In addition, all rates of injected material significantly reduced soil compaction in the E– and B–horizons (15 to 45 cm). Broadcast application of compost significantly increased soil organic matter content 6 and 12 weeks after planting proportional to the compost application rate. In addition, soil nitrogen content was significantly higher in the broadcast application plots 6 weeks after planting. MSW compost (broadcast or injected) significantly increased plant N, P, and K contents compared to no compost application. Increases in plant nitrogen were proportional to application rates. In addition, injected application increased plant sulfur compared to no compost application. All rates of compost (injected or broadcast applications) significantly increased cotton lint yield compared to no compost application. Yield increase was proportional to application rates. For the 26.9–Mg/ha injected application treatment, yield increases were 23, 24, and 44% in 1997, 1998, and 1999, respectively, compared to no compost application. Vitazyme increased plant N, P, and K contents with no effects on Ca, Mg, and S. Vitazyme increased cotton lint yield 35 kg/ha or 3%. In addition, soil nitrogen content 6 weeks after planting in plots treated with Vitazyme was 12% higher than no–Vitazyme plots.

Site-Specific Detection and Management of Nematodes

Nematode distribution varies significantly throughout a field and is highly correlated to soil texture and other edaphic factors. Field-wide application results in nematicides being applied to areas without nematodes and the application of sub-effective levels in areas with high nematode densities. Efforts to use grid maps as a guide to site-specific application have proven to be too expensive to be cost effective. Recently, the availability of GPS –GIS has allowed the use of soil electrical conductivity systems to rapidly and inexpensively develop cost effective soil texture maps. These maps are used to project where nematodes are likely to occur within a field. Variable-rate application systems for granular and fumigant nematicides have been developed and tied via software to soil texture maps providing a mechanism for the effective delivery of nematicides in a site-specific , variable-rate manner in individual fields. Efforts in South Carolina, Georgia, and Arkansas are further developing this system and refining our knowledge of how soil texture and other edaphic factors affect the distribution of cotton nematodes .

Reflectance-Based Sensor to Predict Visual Quality Ratings of Turfgrass Plots

Turfgrass quality is visually evaluated by human assessors based on a scale of 1 to 9. This evaluation practice is subjective and does not provide accurate and reproducible measure of the turf quality. The aim of this research was to design a portable optical sensor to predict the quality ratings of turfgrass research plots from spectral reflectance. Reflectance data were collected using a dual spectroradiometer covering a spectrum of 350-1050 nm from bermudagrass and bluegrass research plots. Two different regression methods, Multiple Linear Regression (MLR) and Partial Least Squares Regression (PLSR), were used and compared. Two wavelength bands centered at 680 nm (Red) and 780 nm (NIR) were identified since these bands carry useful information in the prediction of turfgrass visual quality. The average Standard Error of Cross Validation (SECV) was found to be about 0.76 and 0.88 by using the model with Red and NIR bands for bermudagrass and bluegrass data sets, respectively. A simple prototype sensor using the two identified bands was fabricated and tested. The prototype sensor predicted the visual quality ratings as well as the spectroradiometer with a SECV of about 0.57 using two bands.

Temporal Dynamics and Electronic Nose Detection of Stink Bug-Induced Volatile Emissions from Cotton Bolls

Management decisions for stink bugs (Pentatomidae) in Bt cotton are complicated by time-consuming sampling methods, and there is a need for more efficient detection tools. Volatile compounds are released from cotton bolls in response to feeding by stink bugs, and electronic nose (E-nose) technology may be useful for detecting boll damage. In this study, we investigated the temporal dynamics of volatile emissions in response to feeding by stink bugs and tested the ability of E-nose to discriminate between odors from healthy and injured bolls. Feeding by stink bugs led to an approximate 2.4-fold increase in volatile organic compound (VOC) emissions. Principal components analysis of E-nose sensor data showed distinct (100%) separation between stink bug-injured and healthy bolls after two days of feeding. However, when E-nose was used to randomly identify samples, results were less accurate (80–90%). These results suggest that E-nose is a promising technology for rapid detection of stink bug injury to cotton.

Spatial Distribution of Reniform Nematode in Cotton as Influenced by Soil Texture and Crop Rotations

Reniform nematode (RN) is an important pest in cotton production. Knowledge of the distribution patterns of RN is essential for selecting sampling strategies and for site-specific management. A 3-year study was conducted in two fields in South Carolina with the purpose of characterizing the distribution of RN using a fine-scale sampling scheme in plots representing different soil textures (field 1), and using a large-scale arbitrary sampling scheme (field 2). Horizontal distribution data showed an aggregated pattern of RN densities at planting and after harvest in both fields each year, with patches ranging from 8 to 12 m. However, a significant neighborhood structure was only detected when suitable hosts (cotton and soybean) were planted. Correlations between RN densities and percent sand and silt were detected, showing nematode densities peaked when sand content was around 60% and declined when sand content increased above 60 to 65%. When fewer samples were taken in the field with more uniform sand content, percentage of sand was a less reliable predictor of RN densities. Vertical sampling showed the highest numbers of RN were found at 15 to 30 cm deep after cotton, but were deeper after a nonhost crop. Understanding distribution patterns of RN within a field may improve the effectiveness of management practices.

Volatile Emissions from Developing Cotton Bolls in Response to Hemipteran Feeding Damage

Hemipteran pests feed directly on cotton fruiting structures (bolls) causing damage to fiber and yield. Herbivore-induced volatile emissions have been well studied with regard to leaf-chewing insects, but no research has examined the release of volatiles from developing cotton bolls in response to damage from piercing-sucking insects. We compared volatile emissions from bolls in response to feeding damage by brown stink bug, Euschistus servus (Say), southern green stink bug, Nezara viridula, (L.), and the leaf footed bug, Leptoglossus phyllopus (L.) under laboratory conditions. Volatile emissions from bolls in response to N. viridula and mechanical damage were investigated under field conditions. Volatiles were collected using dynamic head-space sampling and analyzed by gas chromatography/mass spectrometry. Under laboratory conditions, feeding by hemipterans resulted in a significant increase in volatile emissions from bolls compared with undamaged bolls. Damaged bolls released significantly greater amounts of acyclic terpenes and methyl ketones compared with undamaged bolls. Feeding by different hemipteran species elicited a similar quantitative increase in emissions, but significant differences were detected in the emissions of some individual compounds. Under field conditions, feeding damage by N. viridula resulted in significantly greater volatile emissions compared with undamaged and mechanically-damaged bolls indicating that physical damage alone did not account for the complete blend of volatiles released in response to biotic injury. During feeding, hemipterans inject a complex blend of salivary and digestive enzymes, and some of these compounds may activate volatile induction from bolls. The implication for piercing-sucking damage on biochemical pathways mediating volatile synthesis is discussed.

Developing an Algorithm to Determine the Tillage Depth from Soil Penetrometer Data in Coastal Plain Soils

This study deals with developing an algorithm to determine the optimum tillage depth from soil cone penetrometer data in coastal plain soils. Intensive geo-referenced soil cone penetrometer measurements were obtained and each cone index profile was graphically examined. The results showed 21 different patterns or conditions for the soil cone penetrometer profiles in a Dothan loamy sand soil. An algorithm was developed to assess and find the optimum tillage depth. The limiting cone index value, which prevents the root development, was taken as 2.07 MPa (300 psi). After defining the algorithm, a computer program was written to automate the application of the algorithm for large data sets. The computer program was used to find the optimum tillage depth for the data taken in the two-year study (2000 and 2001). The results of the experimental study clearly indicate that the thickness and the location of the hardpan can be determined from the soil cone penetrometer data. A great amount of variation was observed in the location and the thickness of the hardpan as well as in the optimum tillage depth in both years.