Plant-parasitic nematodes (PPNs) pose a critical challenge in agriculture, particularly when it comes to managing fruit orchards. To address the potential damage, our study aimed to analyze 110 soil samples from pome-fruit tree rhizospheres to identify PPNs. After transferring the samples to the lab, soil washing and nematode extraction were performed using a modified combination of the sieve and centrifugation method by Jenkins, followed by fixation and transfer to glycerin according to De Grisse's method. The results showed that of the 27 identified species, Amplimerlinius parbati, Pratylenchus estoniensis, Rotylenchus bialaebursus, and R. secondus were new records for Iran. A. parbati was distinguished by between four and five head annuli, large stylet with downward knobs, and annulated tail with hemispherical shape. P. estoniensis was identified by two annuli in the lip region, well-developed empty spermathecal, and striated tail tip. R. bialaebursus possessed a rounded lip region with four annuli, phasmids in between nine and 12 annuli anterior to the anus, and a rounded tail with between six and eight annuli. R. secondus was recognized by conoid and slightly offset labial region without/with faint annulation, stylet pointed and less than 30 mu m, rounded tail and vulva situated at 50-70%. Subsequently, the potential threat of the species to fruit orchards is discussed.

Identifying soil erosion-prone zones in an ungauged river basin is crucial for devising and implementing timely soil protection measures to mitigate soil degradation and protect soil quality. Soil erosion damages the fragile ecosystem, decreases soil fertility, and reduces reservoir water storage, thereby impacting food production. The prime motive of the current research work is to assess and categorize on the basis of priority the sub-watersheds (SWs) susceptible to substantial soil erosion in the Ponnaniyar River basin (an ungauged river basin) based on the morphometric parameters that impact soil erosion. To achieve this research objective, four multi-criteria decision-making (MCDM) approaches based on the outranking approach and synthesis method are adopted to facilitate the decision-making process by considering an integrated and balanced assessment of multiple complex parameters for devising effective soil conservation measures to minimize soil erosion. Cartosat-1 digital elevation model (DEM) is employed to extract eighteen morphometric parameters under linear, shape, areal, relief and hypsometric aspects. The priority of SWs obtained by different MCDM techniques is evaluated using percentage of variation and intensity of variation. The outcomes show that the MABAC method is effective in prioritizing SWs with the least percentage of variation (59.61%) and intensity of variation (4.397). It is also found to be the best method for integration with the RSS method for determining SW priority with a root sum of squares value of 43. SW1 is identified to be highly vulnerable to soil erosion with a grade average value of 1.00 followed by SW2 (3.00), SW3 (3.25) and SW13 (5.00), requiring immediate implementation of watershed planning and management measures to control the extent of soil erosion and safeguard soil resources.

The identification of areas prone to soil erosion in ungauged river basins is crucial for timely preventive measures, as erosion causes significant damage by lowering soil productivity and filling reservoirs with sedimentation. This study proposes a novel approach to prioritize sub-watersheds (SWs) in Ponnaniyar river basin. It utilizes different combinations of five objective-based weighting methods and seven Multi-criteria Decision Making (MCDM) techniques under outranking and synthesis methods with soil loss, morphometry, land use/land cover (LULC), and topography parameters. The results obtained from different hybrid models are validated using metrics like percentage and intensity of change. The findings reveal that MW-PROMETHEE (53.85%) and CRITIC-WASPAS (8.31) perform best in prioritizing areas based on morphometry, while CRITIC-TOPSIS (48.35% and 7.58) is more effective in prioritizing areas based on land use/land cover (LULC) and topography. The grade average method is used to integrate the rankings from 71 models: 35 based on morphometry, 35 based on LULC, and 1 based on the RUSLE model. The analysis identifies SW2 with a grade value of 4.34 as severely affected by soil erosion, followed by SW11 (5.45), SW5 (5.56), and SW9 (5.68), all falling within the very high priority level. This study recommends implementing appropriate water harvesting structures, which might be helpful in mitigating soil degradation, promoting soil conservation, and ensuring sustainable agricultural productivity.