Improving the soil quality in arid agro-ecosystems requires a greater understanding of how the time-of-sampling and management affect the soil measurements. We evaluated the selected soil quality indicators on samples collected at a 0–0.15 m depth, and at various sampling dates of the year, corresponding to the fall of 2015, winter of 2015/2016, spring of 2016, and the summer of 2016. The three crop management systems sampled included alfalfa (Medicago sativa), upland cotton (Gossypium hirsutum), and pecan (Carya illinoinensis). The soil properties measured included the wet aggregate stability (WAS), mean weight diameter of dry aggregates (MWD), dry aggregates greater than 2 mm (AGG >2 mm), dry aggregates less than 0.25 mm (AGG <0.25 mm), available water capacity (AWC), soil organic matter (SOM), permanganate oxidizable carbon (POXC), soil bulk density (BD), soil electrical conductivity (EC), pH, nitrate-nitrogen (NO3-N), extractable potassium (K), extractable phosphorus (P), calcium (Ca), magnesium (Mg), sodium adsorption ratio (SAR), and micronutrients (zinc, iron, copper, and manganese). Out of the 21 soil measurements, 15 varied significantly with the time-of-sampling within a year, although there were no consistent trends in variability. However, only a few measurements differed significantly with the crop management practices tested. Wet aggregate stability, MWD, AWC, and BD were significantly higher in the summer, while POXC and SOM were significantly higher in the fall and winter, respectively. Soil quality indicators such as NO3-N, K, and P decreased significantly during the spring. This study shows that the seasonal variability of the soil measurements can be significant in the arid agro-ecosystems, with the magnitude of variation depending on the measurement type. The soil managers in the region need to account for this variability, in order to be able to assess the changes in the soil quality. Also, because of the variability that can occur across the different sampling dates within a year, it is advisable to sample during the same period every year, for a consistent interpretation of the directional changes of the soil quality indicators.

Visible near-infrared reflectance spectroscopy (VNIRS) and laser-induced breakdown spectroscopy (LIBS) are potential methods for the rapid and less expensive assessment of soil quality indicators (SQIs). The specific objective of this study was to compare VNIRS and LIBS for assessing SQIs. Data was collected from over 140 soil samples taken from multiple agricultural management systems in New Mexico, belonging to arid and semiarid agroecosystems. Sampled sites included New Mexico State University Agricultural Science Center research fields and several commercial farm fields in New Mexico. Partial least squares regression (PLSR) was used to establish predictive relationships between spectral data and SQIs. Fifteen soil measurements were modeled including the soil organic matter (SOM), permanganate oxidizable carbon (POXC), total microbial biomass (TMB), total bacteria biomass (TBB), total fungi biomass (TFB), mean weight diameter of dry aggregates (MWD), aggregates 2–4 mm (AGG > 2 mm), aggregates < 0.25 mm (AGG < 0.25 mm), wet aggregate stability (WAS), electrical conductivity (EC), calcium (Ca), magnesium (Mg), sodium (Na), and iron (Fe). Overall, calibrations based on measurements irrespective of locations performed better for LIBS and combined VNIRS-LIBS. Measurements separated according to locations highly improved the quality of prediction for VNIRS as compared to combined locations. For example, the prediction R² values for regression of VNIRS were 0.19 for SOM, 0.30 for POXC, 0.24 for MWD, 0.15 for AGG > 2 mm, and 0.13 for EC in combined datasets irrespective of location. When separated according to locations, for one of the locations, the predictive R² values for VNIRS were 0.48 for SOM, 0.70 for POXC, 0.67 for MWD, 0.60 for AGG > 2 mm, and 0.51 for EC. The prediction values varied with the sampling time for both LIBS and VNIRS. For example, the prediction values of some SQIs using VNIRS were higher in samples collected in winter for measurements, including SOM (0.90), MWD (0.96), WAS (0.66), and EC (0.94). Using the VNIRS, the corresponding predictive values for the same SQIs were lower for samples collected in the fall (SOM (0.61), MWD (0.45), WAS (0.46), and EC (0.65)). While this study illustrates the prospects of VNIRS and LIBS for estimating SQIs, a more comprehensive evaluation, using a larger regional dataset, is required to understand how the site and soil factors affect VNIRS and LIBS, in order to enhance the utility of these methods for soil quality assessment in arid and semiarid agroecosystems.

A two-year field study was conducted in sandy loam soil to evaluate the impacts of biochar on soil quality and the growth and yields of pinto bean (Phaseolus vulgaris) and sorghum–Sudan (Sorghum × drummondii). A wood-derived commercial biochar was applied at three rates to pinto bean (PB) and sorghum–Sudan (SS) plots. The biochar application rates applied annually for two years to PB plots were 0, 2.2, and 11.2 Mg ha⁻¹, whereas the rates for SS plots were 0, 3.4, and 6.7 Mg ha⁻¹. Crop growth and harvest parameters were evaluated. Assessed soil measurements included pH, electrical conductivity, available nutrients, soil organic matter (SOM), permanganate oxidizable carbon (POXC), soil aggregates, and volumetric soil moisture content. The results showed no significant differences in plant growth parameters and yields over the two growing seasons for both PB and SS. Compared to the control treatment, the biochar at 11.2 Mg ha⁻¹ in PB plots improved soil moisture retention after irrigation by 19% in the first year and 25% in the second year. The SOM in the SS plot at 6.7 Mg ha⁻¹ biochar rate was higher (1.02%) compared to the control plot (0.82%), whereas a similar increase was not observed in the PB plot. Although biochar rates did not affect most of the soil measurements, there were significant changes in soil properties over time, regardless of biochar treatments: POXC increased in the PB and SS plots; SOM increased in the SS plot; and electrical conductivity, sodium adsorption ratio, and most soil micronutrients decreased. This research was conducted over two years; the effects of biochar can persist for much longer, indicating the need for longer-term biochar field studies in arid agroecosystems.

Reducing tillage has become necessary in irrigated, arid cropping systems in southwestern USA, to address soil degradation and erosion problems associated with intensive soil tillage. A study was conducted in arid southwestern USA, to compare a reduced tillage method (strip tillage) to two conventional tillage methods (plow tillage and raised bed tillage) for irrigated upland cotton (Gossypium hirsutum) production. Strip tillage (ST) was established in a single pass by a strip tillage equipment, while the plow tillage (PT) consisted of plowing, disking the soil twice, subsoiling and harrowing. The raised bed tillage (BT) consisted of all the tillage operations under PT method, with an additional tillage event to shape the beds. Crop and soil parameters were assessed during the growing seasons. Soil physical and biological measurements were assessed at the beginning of the trial before planting, and at the end of each cropping season. Results show no significant differences in cotton yield and fiber quality parameters under the tillage systems tested. Out of the soil physical measurements assessed, the cone index (CI) significantly differed with tillage systems during the mid-season assessments, with BT generally having better CI than ST and PT. Other physical measurements were not significant with tillage, but significantly declined over time irrespective of tillage treatments. Out of the soil biological measurements assessed, the total fungal biomass and the arbuscular mycorrhizae fungi biomass were significant with tillage, with ST and BT having higher measurements than PT. In contrast to soil physical measurements that declined, most of the soil biological measurements improved over time. Comparing some soil biological measurements at the beginning to the end of the trial across the tillage treatments, the total microbial biomass increased from 714 to 3565 ng/g, the total bacterial biomass increased from 321 to 1478 ng/g, and the total fungal biomass increased from 84 to 436 ng/g. This study shows that ST can perform adequately for sustainable cotton production in an irrigated arid region of United States.