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For the first time, renewable carbon (RC) from bamboo-biomass modified with copper nanoparticles (CuNPs) has been prepared via a chemical reduction step for the electroanalytical detection of dopamine (DOP), fluoxetine (FXT) and escitalopram (EST). The synthesized RCCuNPs nanocomposite morphology and structural composition were characterized by FEG-SEM along with EDS analysis. The electroanalytical behavior of the target analytes was investigated by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The analytical range of detection of DOP, FXT, and EST was 0.05–5.0, 0.1–10, and 0.02–5.0 µmol L−1, respectively. The limits of detection (LOD) were found to be 0.04, 0.05, and 0.25 µmol L−1, respectively. In addition, the standard addition method was used for the detection and recovery of DOP in synthetic human urine and EST in tap water samples. The synergistic effect of CuNPs coupled with the highly porous RC material provided a sensitive, low-cost, and easy to prepare sensing platform for detecting target analytes in clinical and environmental samples.

Precision weed management technology has immense potential for treating weed species at a small scale. To this end, however, crop and weeds must be recognized. One approach to this involves identification of reflectance signatures of crops and weeds that differ in the visible and near-infrared (NIR) wavelength region. Reflectance spectra were used for the detection of cheat (Bromus secalinus L.), ryegrass (Lolium multiflorum Lam.), and winter wheat (Triticum aestivum L.) under greenhouse conditions. A total of three experiments (two in December 2002 and one in February 2003) were conducted at the Agronomy Research Station, Stillwater, OK. The three species and two N levels were arranged in a completely randomized design with three replications. Spectral readings were taken at Feekes 3 and 5 winter wheat growth stages with a spectrometer. Two spectral measurements were obtained from each pot. The spectral measurements from the three experiments were combined by the two growth stages because preliminary analysis revealed that date of measurement and N levels were not significant. The spectral readings were measured at 1-nm intervals and averaged into 10-nm bandwidths for the wavelengths from 400 to 865 nm. Data were analyzed using a discriminant analysis procedure. The discriminant function with the band combinations 515/675, 555/675, and 805/815 resulted in the best overall correct classification (94%) of observations at Feekes 3, while for spectral data at Feekes 5 the discriminant function with the band combinations 755 and 855/ 675 resulted in 66.7% overall correct classification of observations. In several instances, ryegrass was classified as either cheat or winter wheat, while cheat was classified as rye. Cheat was not classified as winter wheat in most instances. This suggests that it is possible to identify cheat in winter wheat using wavelength ratios developed from spectral readings in 10-nm bands between 500 and 860 nm., TODAY SITE SPECIFIC application technology or precision farming is becoming an integral part of agriculture. One aspect of site specific application technology involves weed and nutrient management. Precision weed and [...]

52 DEVELOPING A NEW METHOD FOR CITIZEN SCIENTISTS TO ASSESS SANDY BEACH ECOSYSTEMS Traditionally managed as recreation areas, beaches are also important natural ecosystems, a link between marine and terrestrial [...]

Grunion runs are part of the cultural heritage of southern Californians. These surfing silversides spawn out of water in spectacular summer runs on sandy beaches around midnight. Grunion runs occur at predictable times and dates associated with the highest nighttime tides from April to July. These marine fish are presumed to remain near shore at other times, but are rarely taken in trawls or by any standard fish population assessment methods. Prior to 2001, grunion populations had not been monitored for over 50 years. Because they oviposit at high tide, their eggs incubate out of water, buried in the sand of some of the most heavily used urban beaches in this populous area. In 2001, uncertainty about the grunion population status in San Diego prompted an outpouring of citizen concern regarding the possible effects of mechanized beach grooming on grunion nests, and a call for data by the city. We developed a protocol for training volunteers to attend predicted runs at specific times and locations, and to report their sightings via an interactive web data acquisition form. With the help of hundreds of volunteers, we monitored 10 sites on San Diego beaches for the past three years. Volunteers saw large numbers of grunion spawning in many locations on the city shoreline. Spawning activity peaked in late April and late May in all three years. The duration of the runs and numbers offish varied significantly between sites and over the season, indicating that monitoring must be done consistently and extensively to characterize this ephemeral yet charismatic species. In 2004 our volunteers surveyed grunion in California from San Diego to Monterey Bay. Funded by NOAA Grant NA06RG0142, Calif.. Sea Grant R/CZ-94PD, NFWF, and NSF-DBI 99-87543.

The use of by-plot coefficient of variation (CV) has not been evaluated in precision agricultural work. This study evaluated the relationship between CVs determined from normalized-difference vegetative index (NDVI) sensor readings, plant population, and sensing direction on NDVI values. Randomly selected plots, measuring 1 m 2 (2003) and 3 m 2 (2004), were established for this study. Plots in 2004 were divided into three 1 m 2 subplots with, 0 and 120 kg ha -1 fall-applied N, and 80 kg ha -1 topdress nitrogen (N). Sensor reading of subplots were taken at Feekes 5 and 7 using the Green Seeker hand-held sensor. Results showed that the relationship between vegetative RI (RI NDVI ) and harvest RI (RI Harvest ) improved with increasing CV values. The prediction of RI Harvest was improved when CV was integrated into the RI NDVI calculation. RI Harvest can be better predicted with RI NDVI when the CV of spectral radiance measurements is used in the RI NDVI equation. [ABSTRACT FROM AUTHOR]

The components that define cereal-grain yield potential have not been well defined. The objective of this study was to collect many differing biological measurements from a long-term winter wheat ( Triticum aestivum L.) study in an attempt to better define yield potential. Four treatments were sampled that annually received 0, 45, 90, and 135 kg N ha -1 at fixed rates of phosphorus (P) (30 kg ha -1 ) and potassium (K) (37 kg ha -1 ). Mid-season measurements of leaf color, chlorophyll, normalized difference vegetative index (NDVI), plant height, canopy temperature, tiller density, plant density, soil moisture, soil NH 4 -N, NO 3 -N, organic carbon (C), total nitrogen (N), pH, and N mineralization potential were collected. In addition, soil texture and bulk density were determined to characterize each plot. Correlations and multiple linear-regression analyses were used to determine those variables that can predict final winter wheat grain yield. Both the correlation and regression analyses suggested mid-season NDVI, chlorophyll content, plant height, and total N uptake to be good predictors of final winter wheat grain yield. [ABSTRACT FROM AUTHOR]

Although spring-applied nitrogen (N) has been shown to be most efficient, the technique of delaying all N applications until mid-season, and the resultant effect on maximum yields, has not been thoroughly evaluated. This experiment was conducted to determine if potential yield reductions from early-season N stress can be corrected using in-season N applications. Data from three experimental sites and two growing seasons (six site-year combinations) were used to evaluate three preplant N rates (0, 45, and 90 kg ha -1 ) and a range of in-season topdress N rates. Topdress N amounts were determined using a GreenSeeker hand-held sensor and an algorithm developed at Oklahoma State University. Even when early-season N stress was present (0-N preplant), N-applied topdress at Feekes 5 resulted in maximum or near-maximum yields in four of six site-year combinations when compared with other treatments receiving both preplant and topdress N. [ABSTRACT FROM AUTHOR]

Recently, environmental quality issues related to sulfur (S) have made it necessary to reduce its release into the atmosphere in wet or dry forms, which in turn might influence the S requirement of crops. It is anticipated that by 2020, S deposition will decrease by up to 30% in eastern portions of Oklahoma and by 15% throughout the remainder of the state. This change calls for frequent monitoring and evaluation of S nutrition in wheat and other crops. Experiments were conducted at Hennessey and Perkins research stations for a period of seven years starting in the fall of 1996, with the objective of assessing the effect of different levels of elemental and sulfate-S fertilizers on the grain and forage yields of winter wheat in Oklahoma. The experimental design was a randomized complete block with three replications. Four S rates, 0, 56, 112, and 224 kg S ha - 1 , were applied to the plots from 1996 to 2002 as CaSO 4 . Another two rates, 56 and 112 kg S ha - 1 , were included in the trials beginning in 1998 using 92% elemental S. Gypsum, as a source of S for winter wheat, resulted in a greater yield than did elemental S in cases where S fertilizer sources were deemed significant. In six of 14 trials from 1996 to 2002, applied S as CaSO4 significantly increased wheat-grain yields. Observing significant grain and forage yield increases due to applied S was important, but the response was sporadic and unpredictable from one year to the next. [ABSTRACT FROM AUTHOR]

Current methods for making nitrogen (N) recommendations in winter wheat (Triticum aestivum L.) do not adjust for in-season temporal variability of plant available nonfertilizer N sources. The purpose of this study was to compare the use of different N response indices determined in-season (RINDVI and RIPLANTHEIGHT) to the N response index measured at harvest (RIHARVEST). In addition, this study evaluated the use of the in-season response indices for determining topdress N rates for winter wheat. Nine experiments were conducted over two years at eight different locations. A randomized complete block design with nine different treatments and four replications was used at each location. Preplant N source was ammonia nitrate (34-0-0). At Feekes 4-6, RINDVI was measured to determine the topdress N rates. Both RINDVI and RIPLANTHEIGHT were able to predict RIHARVEST (r² = 0.75 and r² = 0.74, respectively). Because the sensor-based approach for making N recommendations relies on information obtained from in-season sensor readings, RINDVI should be used to estimate a site's potential for response to additional N. Use of the response index will allow producers to move away from reliance on preplant application of N and start managing N based on the likelihood of achieving an economical response to N fertilizer. [ABSTRACT FROM AUTHOR]

Knowing the exact stage of growth where expressed plant variability is at a maximum might lead to the identification of times when in-season fertilization could have the greatest impact. One field experiment was initiated to measure daily plant growth and spatial variability in corn (Zea mays L.) over the entire growth cycle using optical sensor readings (normalized difference vegetative index, or NDVI) collected every 0.05 m in length, 0.6 m wide from 4 corn rows, 27 m in length. Averaged over all 4 rows, plants were spaced 21± 7 cm apart. For each row and sensing date, the mean, standard deviation, and coefficient of variation (CV) were computed from the NDVI readings. Eighteen days after planting, NDVI values were near 0.20 and later peaked near 0.81, 54 days after planting at the 10-leaf growth stage (V10). Coefficients of variation were found to peak much earlier, 33 to 35 days after planting at the 6-leaf > 30% at V6 to just under 10% at the 11-leaf growth stage (VII). Immediately following VII, a distinct increase in CVs was found just following the initiation of tasseling (VT), but lasted for only 2 days. Expressed spatial variability was greatest at the V6 growth stage, and this peak in the within-row-by-plant variability may be the precise growth stage at which treating that variability will have the greatest impact. [ABSTRACT FROM AUTHOR]