Effect of microwave radiation on seed mortality of rubber vine (Cryptostegia grandiflora R.Br.), parthenium (Parthenium hysterophorous L.) and bellyache bush (Jatropha gossypiifolia L.)

A trial was undertaken to evaluate the effect of microwaves on seed mortality of three weed species. Seeds of rubber vine (Cryptostegia grandiflora R.Br.), parthenium (Parthenium hysterophorous L.) and bellyache bush (Jatropha gossypiifolia L.) were buried at six depths (0, 2.5, 5, 10, 20 and 40 cm) in coarse sand maintained at one of two moisture levels, oven dry or wet (field capacity), and then subjected to one of five microwave radiation durations of (0, 2, 4, 8 and 16 min). Significant interactions between soil moisture level, microwave radiation duration, seed burial depth and species were detected for mortality of seeds of all three species. Maximum seed mortality of rubber vine (88%), parthenium (67%) and bellyache bush (94%) occurred in wet soil irradiated for 16 min. Maximum seed mortality of rubber vine and bellyache bush seeds occurred in seeds buried at 2.5 cm depth whereas that of parthenium occurred in seeds buried at 10 cm depth. Maximum soil temperatures of 114.1 and 87.5°C in dry and wet soil respectively occurred at 2.5 cm depth following 16 min irradiation. Irrespective of the greater soil temperatures recorded in dry soil, irradiating seeds in wet soil generally increased seed mortality 2.9-fold compared with dry soil. Moisture content of wet soil averaged 5.7% compared with 0.1% for dry soil. Results suggest that microwave radiation has the potential to kill seeds located in the soil seed bank. However, many factors, including weed species susceptibility, determine the effectiveness of microwave radiation on buried seeds. Microwave radiation may be an alternative to conventional methods at rapidly depleting soil seed banks in the field, particularly in relatively wet soils that contain long lived weed seeds.

Net radiation dynamics: performance of 20 daily net radiation models as related to model structure and intricacy in two climates.

We compared daily net radiation (Rn) estimates from 19 methods with the ASCE-EWRI Rn estimates in two climates: Clay Center, Nebraska (sub-humid) and Davis, California (semi-arid) for the calendar year. The performances of all 20 methods, including the ASCE-EWRI Rn method, were then evaluated against Rn data measured over a non-stressed maize canopy during two growing seasons in 2005 and 2006 at Clay Center. Methods differ in terms of inputs, structure, and equation intricacy. Most methods differ in estimating the cloudiness factor, emissivity (e), and calculating net longwave radiation (Rnl). All methods use albedo (a) of 0.23 for a reference grass/alfalfa surface. When comparing the performance of all 20 Rn methods with measured Rn, we hypothesized that the a values for grass/alfalfa and non-stressed maize canopy were similar enough to only cause minor differences in Rn and grass- and alfalfa-reference evapotranspiration (ETo and ETr) estimates. The measured seasonal average a for the maize canopy was 0.19 in both years. Using a = 0.19 instead of a = 0.23 resulted in 6% overestimation of Rn. Using a = 0.19 instead of a = 0.23 for ETo and ETr estimations, the 6% difference in Rn translated to only 4% and 3% differences in ETo and ETr, respectively, supporting the validity of our hypothesis. Most methods had good correlations with the ASCE-EWRI Rn (r2 > 0.95). The root mean square difference (RMSD) was less than 2 MJ m-2 d-1 between 12 methods and the ASCE-EWRI Rn at Clay Center and between 14 methods and the ASCE-EWRI Rn at Davis. The performance of some methods showed variations between the two climates. In general, r2 values were higher for the semi-arid climate than for the sub-humid climate. Methods that use dynamic e as a function of mean air temperature performed better in both climates than those that calculate e using actual vapor pressure. The ASCE-EWRI-estimated Rn values had one of the best agreements with the measured Rn (r2 = 0.93, RMSD = 1.44 MJ m-2 d-1), and estimates were within 7% of the measured Rn. The Rn estimates from six methods, including the ASCE-EWRI, were not significantly different from measured Rn. Most methods underestimated measured Rn by 6% to 23%. Some of the differences between measured and estimated Rn were attributed to the poor estimation of Rnl. We conducted sensitivity analyses to evaluate the effect of Rnl on Rn, ETo, and ETr. The Rnl effect on Rn was linear and strong, but its effect on ETo and ETr was subsidiary. Results suggest that the Rn data measured over green vegetation (e.g., irrigated maize canopy) can be an alternative Rn data source for ET estimations when measured Rn data over the reference surface are not available. In the absence of measured Rn, another alternative would be using one of the Rn models that we analyzed when all the input variables are not available to solve the ASCE-EWRI Rn equation. Our results can be used to provide practical information on which method to select based on data availability for reliable estimates of daily Rn in climates similar to Clay Center and Davis.