Past agricultural management practices have contributed to the loss of soil organic carbon (SOC) and emission of greenhouse gases (e.g., carbon dioxide and nitrous oxide). Fortunately, however, conservation-oriented agricultural management systems can be, and have been, developed to sequester SOC, improve soil quality, and increase crop productivity. Our objectives were to (i) review literature related to SOC sequestration in cotton (Gossypium hirsutum L.) production systems, (ii) recommend best management practices to sequester SOC, and (iii) outline the current political scenario and future probabilities for cotton producers to benefit from SOC sequestration. From a review of 20 studies in the region, SOC increased with no tillage compared with conventional tillage by 0.48 +/- 0.56 Mg C ha(-1) yr(-1) (H(0): no change, p < 0.001). More diverse rotations of cotton with high-residue-producing crops such as corn (Zea mays L.) and small grains would sequester greater quantities of SOC than continuous cotton. No-tillage cropping with a cover crop sequestered 0.67 +/- 0.63 Mg C ha(-1) yr(-1), while that of no-tillage cropping without a cover crop sequestered 0.34 +/- 47 Mg C ha(-1) yr(-1) (mean comparison, p = 0.04). Current government incentive programs recommend agricultural practices that would contribute to SOC sequestration. Participation in the Conservation Security Program could lead to government payments of up to Dollars 20 ha(-1). Current open-market trading of C credits would appear to yield less than Dollars 3 ha(-1), although prices would greatly increase should a government policy to limit greenhouse gas emissions be mandated.

Quantification of the impact of long‐term agricultural land use on soil organic C (SOC) is important to farmers and policymakers, but few studies have characterized land use and management effects on SOC across physiographic regions. We measured the distribution and total stock of SOC to a depth of 20 cm under conventional tillage (CvT), conservation tillage (CsT), and pasture in 87 production fields from the Southern Piedmont and Coastal Plain Major Land Resource Areas. Across locations, SOC at a depth of 0 to 20 cm was: pasture (38.9 Mg ha−1) > CsT (27.9 Mg ha−1) > CvT (22.2 Mg ha−1) (P ≤ 0.02). Variation in SOC was explained by management (41.6%), surface horizon clay content (5.2%), and mean annual temperature (1.0%). Higher clay content and cooler temperature contributed to higher SOC. Management affected SOC primarily at the soil surface (0–5 cm). All SOC fractions (i.e., total SOC, particulate organic C, soil microbial biomass C, and potential C mineralization) were strongly correlated across a diversity of soils and management systems (r = 0.85–0.96). The stratification ratio (concentration at the soil surface/concentration at a lower depth) of SOC fractions differed among management systems (P ≤ 0.0001), and was 4.2 to 6.1 under pastures, 2.6 to 4.7 under CsT, and 1.4 to 2.4 under CvT; these results agree with a threshold value of 2 to distinguish historically degraded soils with improved soil conditions from degraded soils. This on‐farm survey of SOC complements experimental data and shows that pastures and conservation tillage will lead to significant SOC sequestration throughout the region, resulting in improved soil quality and potential to mitigate CO2 emissions.

c-means clustering of remotely sensed (RS) data, and multiple linear regression relating spectral response to Knowledge of surface soil properties is used to assess past erosion soil attributes may be used to evaluate variability in and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to surface soil properties. evaluate high resolution IKONOS multispectral data as a soil-map-The basic relationships between spectral response and ping tool. Imagery was acquired over conventionally tilled fields in soil properties have been well researched. Early studies the Coastal Plain and Tennessee Valley physiographic regions of Alahave shown a negative correlation exists between surbama. Acquisitions were designed to assess the impact of surface crustface TC and reflectance in the visible (VIS) and near infraing, roughness, and tillage on our ability to depict soil property variabilred (NIR) (Baumgardner et al., 1970; Sudduth and Humity. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic mel, 1991; Henderson et al., 1992). Increasing amounts Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic of TC have a darkening effect, consequently reducing Rhodic Paleudults at the Tennessee Valley site. Soils were sampled the amount of energy reflected. Similarly, Coleman and in 0.20-ha grids to a depth of 15 cm and analyzed for percentages of Montgomery (1987) found a strong negative correlation sand (0.05-2 mm), silt (0.002-0.05 mm), clay (Ͻ0.002 mm), citratedithionite extractable Fe, and total C (TC). Four methods of evaluat-(r ϭ Ϫ0.58) between TC and NIR (0.76-0.90 m) reflecing variability in soil attributes were evaluated: (i) kriging of soil at-tance in Vertisols and Alfisols in Alabama's Blackbelt tributes, (ii) cokriging with soil attributes and reflectance data, (iii) region. These authors noted increasing soil water conmultivariate regression based on the relationship between reflectance tent, coincident with increasing TC, tended to depress and soil properties, and (iv) fuzzy c-means clustering of reflectance surface reflectance and mask spectral features of interdata. Results indicate that cokriging with remotely sensed (RS) data est (Johnson et al., 1998). improved field scale estimates of surface TC and clay content com-Soil texture also impacts soil spectral response curves. pared with kriging and regression methods. Fuzzy c-means worked In highly weathered and eroded soil systems of the best using remotely sensed data acquired over freshly tilled fields, Southeastern Coastal Plain and Tennessee Valley physreducing soil property variability within soil zones compared with iographic regions, the sand (0.05-2 mm) fraction is prifield scale soil property variability. marily composed of quartz with lesser quantities of mica, and clay (Ͻ0.002 mm) particles consist of kaolinite, with lesser quantities of hydroxy-interlayered vermiculite, Fe S urface soil properties are often used to assess soil oxides, and gibbsi...

Cotton (Gossypium hirsutum L.) yield and quality responses to irrigation have not been described for conservation management systems that growers are rapidly adopting. We conducted a field experiment from 2001-2003 in the Tennessee Valley near Belle Mina, AL on a Decatur silt loam (fine, kaolinitic, thermic Rhodic Paleudults) to examine how irrigation regimes and tillage systems affect ginning percentage, lint yield, and fiber quality (length, micronaire, strength, and fiber length uniformity). Treatments were arranged with a splitplot structure in a randomized complete block design with three replications. Main plots were a factorial combination of conventional tillage (CT) with and without a fall paratill operation and no surface tillage (NST) following a rye (Secale cereale L.) cover crop with and without a fall paratill operation. Subplots were irrigation regimes (0, 2.7, 5.4, and 8.1 mm d 21 ). Ginning percentage increased 2% following CT in 1 of 3 yr (2002) while irrigation improved ginning percentage in 2 of 3 yr (2002 and 2003). The NST systems increased lint yields 13% in 2003 compared with CT systems while irrigation increased yields 46 and 32% over nonirrigated yields in 2002 and 2003, respectively. Fiber properties were affected by tillage systems, primarily in 2002. Irrigation regimes affected length, micronaire, and fiber length uniformity in 2002 and 2003.Fall paratilling had no effect on any measured variable, except for an inconsistent difference between tillage systems for fiber length uniformity. An irrigated conservation system, utilizing a cover crop, can improve cotton yields and positively influence fiber characteristics in the Tennessee Valley.

Unmanned aircraft systems (UAS) allow us to collect aerial data at high spatial and temporal resolution. Raw images are taken along a predetermined flight path and processed into a single raster file covering the entire study area. Radiometric calibration using empirical or manufacturer methods is required to convert raw digital numbers into reflectance and to ensure data accuracy. The performance of five radiometric calibration methods commonly used was investigated in this study. Multispectral imagery was collected using a Parrot Sequoia camera. No method maximized data accuracy in all bands. Data accuracy was higher when the empirical calibration was applied to the processed raster rather than the raw images. Data accuracy achieved with the manufacturer-recommended method was comparable to the one achieved with the best empirical method. Radiometric error in each band varied linearly with pixel radiometric values. Smallest radiometric errors were obtained in the red-edge and near-infrared (NIR) bands. Accuracy of the composite indices was higher for the pixels representing a dense vegetative cover in comparison to a lighter cover or bare soil. Results provided a better understanding of the advantages and limitations of existing radiometric calibration methods as well as the impact of the radiometric error on data quality. The authors recommend that researchers evaluate the performance of their radiometric calibration before analyzing UAS imagery and interpreting the results.