Thermal inactivation kinetics of Salmonella and Enterococcus faecium NRRL B-2354 on dried basil leaves.

The enhanced heat resistance of Salmonella developed at low water activity makes it a serious challenge to eliminate them during thermal processing. The objectives of this research are to (i) investigate the effect of water activity on thermal inactivation of Salmonella cocktail (Agona, Tennessee, Mbandaka, Montevideo, and Reading) in dried basil leaves, and (ii) evaluate Enterococcus faecium NRRL B-2354 as an appropriate surrogate for Salmonella in dried basil leaves. Dried basil leaves, inoculated with a Salmonella cocktail and E. faecium separately, were equilibrated to different water activities (aw: 0.40, 0.55, and 0.70) in a humidity-controlled chamber. The basil samples were packed (1.6 ± 0.1 g) in aluminum pouches and thermally treated at 70, 75, and 80 °C using a dry heating method for 0-180 min to obtain the thermal death curve. The microbial survival data was fit using two primary models (Log-linear and Weibull model). Results from AICc showed that the log-linear model fits well for thermal inactivation of both microorganisms. As the aw decreases from 0.70 to 0.40 at 75 °C, the D-value increases from 3.30 to 9.14 min for Salmonella and 6.53 to 14.07 min for E. faecium. Based on the AICc values, the modified Bigelow model fits the D-values better than the response surface model for both the microorganisms. The kill ratio of surrogate to pathogen ranged from 1.4 to 2.8, indicating that it is a conservative surrogate for Salmonella for performing validation of the thermal pasteurization process. The identification of suitable surrogate and development of modified Bigelow model will help the spice industry in developing the thermal processes for improving the safety of basil leaves.

Surface Energy Balance Based Evapotranspiration Mapping in the Texas High Plains.

Agriculture on the Texas High Plains (THP) uses approximately 89% of groundwater withdrawals from the Ogallala Aquifer. Consequently, groundwater levels are declining faster than the recharge rate. Therefore, efficient agricultural water use is essential for economic viability and sustainability of the THP. Accurate regional evapotranspiration (ET) maps would provide valuable information on actual crop water use. In this study, METRIC (Mapping Evapotranspiration at High Resolution using Internalized Calibration), a remote sensing based ET algorithm, was evaluated for mapping ET in the THP. Two Landsat 5 Thematic Mapper images acquired on 27 June (DOY 178) and 29 July (DOY 210) 2005 were used for this purpose. The performance of the ET model was evaluated by comparing the predicted daily ET with values derived from soil moisture budget at four commercial agricultural fields. Daily ET estimates resulted with a prediction error of 12.7±8.1% (mean bias error ± root mean square error) on DOY 178 and -4.7±9.4% on DOY 210 when compared with ET derived from measured soil moisture through the soil water balance. These results are good considering the prevailing advective conditions in the THP. METRIC have the potential to be used for mapping regional ET in the THP region. However, more evaluation is needed under different agroclimatological conditions.

Models for hydrologic design of evapotranspiration landfill covers.

The technology used in landfill covers is changing, and an alternative cover called the evapotranspiration (ET) landfill cover is coming into use. Important design requirements are prescribed by Federal rules and regulations for conventional landfill covers but not for ET landfill covers. There is no accepted hydrologic model for ET landfill cover design. This paper describes ET cover requirements and design issues, and assesses the accuracy of the EPIC and HELP hydrologic models when used for hydrologic design of ET covers. We tested the models against high-quality field measurements available from lysimeters maintained by the Agricultural Research Service of the U.S. Department of Agriculture at Coshocton, Ohio, and Bushland, Texas. The HELP model produced substantial errors in estimating hydrologic variables. The EPIC model estimated ET and deep percolation with errors less than 7% and 5%, respectively, and accurately matched extreme events with an error of less than 2% of precipitation. The EPIC model is suitable for use in hydrologic design of ET landfill covers.