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Seawater intrusion associated with climate change and sea level rise (SLR) has been postulated for the last decade that causes negative impact on worldwide environmental resources. In Thailand, however; the pertaining information to its effect on soil properties in agricultural areas has not been clearly reported yet. Hence, this study aimed to investigate the seawater intrusion effect on soil properties in agricultural areas of Nonthaburi Province, Thailand. Five study locations, which anticipated to be affected by seawater intrusion, were selected based on the different distances from the Chao Phraya River. Soil morphological properties at depth of 0-15 and 15-30 cm were recorded, besides disturbed soil samples at depth of 0-15, 15-30, 30-60, 60-90 and 90-120 cm were collected to determine the soil physical and chemical properties. Additionally, the soil electrical conductivity (ECe) and sodium adsorption ratio (SAR) analyses demonstrating soil salinity and sodicity were monthly conducted from March 2018 to February 2019 and their annual average values were calculated. The results revealed that all soils were deep to very deep, consisted of silty clay, clay textures, and its field soil pH varied from 6.0-8.0. Soil saturated hydraulic conductivity rating exhibited that it was very slow to moderate. ECe and SAR values of these soils ranged from 0.21-4.38 dS m-1 and 8.29-41.89 consecutively, which trended to increase from its annual average during March and April 2019 as well as July and August 2019. These results suggested that seawater intrusion could be presumptively regarded as a co-factor affecting the variability of soil salinity and sodicity occurring at the interval of insufficient freshwater content for forcing seawater. The implementation strategies for freshwater management and planning are required to prevent future potential seawater intrusion.

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The effects on soil properties were studied following sugarcane burning during harvesting based on the analysis of soil properties and the number of microorganisms. The soil bacterial community structure was observed using metagenomics. It was found that burned sugarcane harvesting reduced the soil moisture and total nitrogen contents and decreased the numbers of bacterial fungi and actinomycetes. Furthermore, there were decreased numbers of nitrogen-fixing and phosphate-solubilizing bacteria beneficial to plants. The Firmicutes phylum (46.79%) was found abundantly in the soil after burned sugarcane harvest. Paenibacillus (34.20%) and Bacillus (9.19%) were dominant at the genus level. On the other hand, in the soil after unburned sugarcane harvest, the diversity index was higher than that after burned sugarcane harvest. Actinobacteria (25.92%) dominated at the phylum level, and Candidatus koribacter, Gaiella, Pseudolabrys, and Sphingomonas dominated at the genus level in the unburned plots. Changing the bacterial community resulted in a change in correlation with soil properties. Therefore, the impacts from burned sugarcane harvesting should be realized, specifically that soil physiochemical and biological properties are degraded (except for some groups of bacteria) along with their functions in the soil.

Information to aid the selection of suitable cultivated areas remains meager for mung bean, despite it being a socio-economically important legume crop in Thailand. Hence, a user-friendly soil assessment tool is required to help properly choose planting areas. We aimed to provide a decision support system for mung bean cultivation in central Thailand. Soil suitability classes were performed using relevant factors and data essential for mung bean cultivation in 22 provinces in central Thailand. A decision support system was developed as soil map and mobile phone application using data based on soil suitability classes. Information of mung bean growth and yield grown in experimental fields with different soil suitability classes was used for preliminary validation. The main areas were very suitable (S1) and moderately suitable (S3) for mung bean plantation, accounting for 1,319,841 and 1,327,804 ha, respectively. The number of pods per plant and yield per plant of mung bean were higher in S1 areas (12.83–16.65 pods per plant and 8.35–12.43 g/plant, respectively) than in S3 areas. The mung bean yield was also greater in S1 areas (1613.8–2158.7 kg/ha) than in S3 areas (735.8–1138.6 kg/ha). The findings suggest the possibility of using developed decision support system.