Monitoring and mapping of U.S. croplands has long been a primary goal of many users of earth observation satellite data. The advantages of using low spatial and high temporal resolution data are (i) increased ability to monitor the phenological change of crop plants, and (ii) the possibility of generating consistent large area crop cover maps. This study investigates the potential of 500-m MODIS (MODerate Resolution Imaging Spectroradiometer) data in estimating corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] area for the dominant production areas of the USA. To avoid cloud cover, MODIS 32-day composites for all land bands, normalized difference vegetation index (NDVI), and land surface temperature (LST), were used covering March 2002 to February 2003. These time-sequential images were further composited to produce 279 annual time-integrated metrics. Using USDA-NASS Cropland Data Layers (CDL) as subpixel training data, percentage soybean and corn cover per 500-m pixel was calculated and accuracy was assessed at national, state, and county scales using data from the 2002 NASS Census of Agriculture. When these estimates were compared with the NASS Census, r 2 values for corn, soybean, and combined corn and soybean areas were 0.957, 0.949, and 0.984 at the state level, respectively. At the national scale, MODIS estimates of corn and soybean cover differed by 6 and 4%, respectively. Results indicate a robust potential for using MODIS in crop type monitoring applications.

Oral lichen planus (OLP) is a chronic inflammatory oral mucosal disease that occurs more frequently in middle-aged and elderly female patients. Previous studies indicate that OLP is a T-cell dysfunction-induced localized autoimmune disease. Clinically, six types of OLP, namely reticular, papular, plaque-like, atrophic/erosive, ulcerative, and bullous types, can be identified. OLP more commonly affects buccal mucosa, tongue, and gingiva. It always has a bilateral and symmetric distribution of the oral lesions. Plaque-like and atrophic/erosive OLP may be misdiagnosed as oral leukoplakia and oral erythroleukoplakia, respectively. Our previous study found serum autoantibodies in 195 (60.9%) of the 320 OLP patients. Specific serum anti-nuclear, anti-smooth muscle, anti-mitochondrial, gastric parietal cell, thyroglobulin, and thyroid microsomal autoantibodies are present in 28.1%, 8.4%, 1.6%, 26.3%, 21.3%, and 24.4% of 320 OLP patients, respectively. Furthermore, we also discovered that 21.9%, 13.6%, 7.1%, 0.3%, and 14.8% of 352 OLP patients have hemoglobin, iron, vitamin B12, and folic acid deficiencies, and abnormally high serum homocysteine level, respectively. Therefore, it is very important to examine the serum autoantibody, hematinic and homocysteine levels in OLP patients before starting the treatments for OLP patients. Because OLP is an immunologically-mediated disease, corticosteroids are the drugs of choice for treatment of OLP.

Interactions between water and N may impact remote-sensingbased N recommendations. The objectives of this study were to determine the influence of water and N stress on reflectance from a corn (Zea mays L.) crop, and to evaluate the impacts of implementing a remote-sensing-based model on N recommendations. A replicated N and water treatment factorial experiment was conducted in 2002, 2003, and 2004. Yield losses due to water (YLWS) and N (YLNS) stress were determined using the 13 C discrimination (D) approach. Reflectance data (400-1800 nm) collected at three growth stages (V8-V9, V11-VT, and R1-R2) were used to calculate six different remote sensing indices (normalized difference vegetation index [NDVI], green normalized vegetation index, normalized difference water index [NDWI], N reflectance index, and chorophyll green and red edge indices). At the V8-V9 growth stage, increasing the N rate from 0 to 112 kg N ha 21 decreased reflectance in the blue (485 nm), green (586 nm), and red (661 nm) bands. Nitrogen had an opposite effect in the near-infrared (NIR, 840 nm) band. At the V11-VT growth stage, reflectance in the blue, green, and red bands were lower in fertilized than unfertilized treatments. At the R1-R2 growth stage, YLWS was highly correlated (r 5 0.58, P 5 0.01) with red reflectance and NDVI (r 5 20.61, P 5 0.01), while YLNS was correlated with all of the indices except NDVI. A remote sensing model based on YLNS was more accurate at predicting N requirements than models based on yield or yield plus YLWS. These results were attributed to N and water having an additive effect on yield, and similar optimum N rates (100-120 kg N ha 21 ) for both moisture regimes.

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The corn (Zea mays L.)–based ethanol carbon footprint is impacted by many factors including the soil's C sequestration potential. The study's objective was to determine the South Dakota corn‐based ethanol surface SOC sequestration potential and associated partial C footprint. Calculated short‐term C sequestration potentials were compared with long‐term sequestration rates calculated from 95,214 producer soil samples collected between 1985 and 2010. National Agricultural Statistics Service (NASS) grain yields, measured root/shoot ratios and harvest indexes, soil organic C (SOC) and nonharvested C (NHC) first‐order rate constants, measured SOC benchmarks [81,391 composite soil samples (0–15 cm) collected between 1985 and 1998], and 34,704 production surveys were used to calculate the short‐term sequestration potentials. The SOC short‐term, area weighted sequestration potential for the 2004 to 2007 time period was 181kg C (ha × yr)−1. This relatively low rate was attributed to a drought that reduced the amount of NHC returned to soil. For the 2008 to 2010 time period, the area weighted short‐term sequestration rate was 341 kg (ha × yr)−1. This rate was similar to the long‐term measured rate of 368 kg C (ha × yr)−1. Findings from these independent SOC sequestration assessments supports the hypothesis that many of the regions surface soils are C sinks when seeded with corn. Based on short‐term C sequestration rates, corn yields, and the corn conversion rate to ethanol, the area weighted surface SOC footprints for the 2004 to 2007 and 2008 to 2010 time periods was –10.4 and –15.4 g CO2 equ MJ−1, respectively.

Techniques for measuring soil organic C (SOC) turnover in production fields are needed. The objectives of this study were to propose and test nonisotopic and 13 C stable isotopic techniques for assessing SOC turnover. Based on SOC equilibrium and mass balance relationships, an equation was derived: NHC/SOC initial 5 [1/(SOC 3 k NHC )] (dSOC/dt) 1 k SOC /k NHC , where dSOC/dt is the annual change in SOC, NHC is nonharvested C returned to soil, k SOC is the annual mineralization rate of SOC, and k NHC is the annual mineralization rate of NHC. This equation was used to calculate maintenance rates. An isotopic approach based on simultaneously solving the equations was developed to determine C budgets:and (iv) SOC final 5 SOC retained 1 PCR incorp , where e is the Rayleigh fractionation constant, PCR incorp is the amount of NHC incorporated into SOC final with D PCR being the associated 13 C discrimination (D) value, and SOC retained is the amount of SOC initial retained in the soil after mineralization with D SOC retained being the associated D value.Isotopic and nonisotopic approaches were tested on a production field where aboveground corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yields were measured with a yield monitor and soil samples collected from a slightly offset grid (30 m) in 1995 and 2003 were analyzed for organic C and D. The nonisotopic approach showed that maintenance rates increased with SOC and that an accurate measure of NHC was required to calculate maintenance requirements. Sensitivity analysis of the isotopic approach showed that calculated budgets were sensitive to 13 C discrimination during SOC mineralization. If 13 C discrimination during SOC and NHC mineralization did not occur (e 5 0), then 14.9 and 7.6% of the SOC measured in 1995 (SOC initial ) was mineralized, and 7420 and 2780 kg C ha 21 of NHC were incorporated into SOC final in the 523.4-to 527.3-and 527.3-to 529.2-m elevation zones, respectively. If 13 C discrimination occurred (e 5 22.52%) during SOC mineralization, then the calculated amount of SOC mineralized and the amount of new C incorporated into SOC were reduced.

sponsive categories (91-m grid) and a different recommendation for fields in the responsive range (61-m grid).The efficiency of the management zone approach to improve fertil-Other problems with grid-point sampling are that imizer recommendations relies on accurately locating zone boundaries. portant information may be missed when grid distancesThe objective of this study was to determine the impact of different techniques of identifying management zones on soil NO Ϫ 3 -N and are too large, and many farmers perceive that grid-point Olsen-P (sodium bicarbonate extractable-P) sampling variability. Soil sampling is not profitable. samples were collected on a 60 by 60 m or denser grid, in three fields Grid-cell sampling is an approach where a composite (65, 53, and 40 ha). These samples were analyzed for NO Ϫ 3 -N and sample is collected from a block with a specified size Olsen-P. Soil nutrient data was used to simulate the effect of different (Wollenhaupt et al., 1994). The sample from each block techniques to identify P and N management zone boundaries. Apis analyzed and the resulting value represents the average proaches evaluated for locating management zone sampling boundvalue of the cell. Many current traditional soil sampling aries included: (i) sampling areas impacted by old homesteads or strategies contain some aspect of grid-cell sampling. Feranimals separately from the rest of the field; (ii) sampling different guson et al. (1998) and Buchholz (1999) recommended grid cells; (iii) use of geographic information systems (GIS) or cluster that in Nebraska and Missouri, respectively, the largest analysis to identify zones based on apparent electrical conductivity (EC a ), elevation, aspect, and distance (connectedness); and (iv) sam-sampling area in a field should be 8 ha or less. In Monpling each soil series separately. An F statistic was used to determine if tana, Jacobsen (1998) recommended that the largest the sampling approach reduced nutrient sampling variability. Results sampling area should be 40 ha. suggested that: (i) old homesteads or areas impacted by animals should The management zone approach is based on the hybe sampled separately from the rest of the field; (ii) grid-cell sampling pothesis that a field is a mosaic of different habitats was more consistent in reducing within zone soil-test variability than with each having unique characteristics that influence the other techniques tested; and (iii) zones that are not continuous soil properties and management (Doerge, 1999; Fleming should be sampled and managed separately. et al. , 2000). Information that can be used to identify the different management zones include (i) prior experience, (ii) yield maps, (iii) soil survey maps, (iv) topogra-