Mohammed Nasir Omer, New Mexico State University, Las Cruces, NM, Omololu J. Idowu, MSC 3AE, PO Box 30003, New Mexico State University, Las Cruces, NM, April L. Ulery, Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, Dawn VanLeeuwen, Applied Statistics & International Business, NMSU, Las Cruces, NM and Steven J. Guldan, New Mexico State University, Alcalde, NM
A study was conducted in New Mexico to assess potential soil quality indicators across Major Land Resources Areas (MLRA) that are used for agriculture. Three crop management systems (CMS) [tree crops, field crops and vegetable crops] were sampled at two depths (0-0.15 and 0.15 – 0.30 m) in the fall of 2016 within six MLRA. Four fields per crop management system were sampled, making a total of 12 sampled fields for each MLRA. Soil physical measurements assessed included the water stable aggregates (WAS), mean weight diameter (MWD) of dry aggregates, available water capacity and field bulk density. Soil biological measurements included the soil organic matter, permanganate oxidizable carbon (POXC), total microbial biomass, total fungi biomass, total bacteria biomass and fungi to bacteria ratio. Soil chemical measurements analyzed included the pH, electrical conductivity, sodium adsorption ratio, soil extractable potassium and micronutrients. Results show significant differences in several soil measurements across MLRA and CMS. There were more significant differences of indicator measurements across MLRA than across CMS. Indicators that were significantly different across both MLRA and CMS included POXC, total microbial biomass, total bacterial biomass and total fungal biomass. There were many significant correlations between physical, chemical and soil biological parameters measured, with POXC, soil organic matter, WAS, and the MWD having strong positive correlations with several microbial parameters that were measured. The strong intercorrelation among several variables measured offers the possibility of selecting a representative minimum dataset of soil quality indicators that can be used for soil quality assessment in arid regions.