A quantitative and qualitative assessment of sugar beet genotype resistance to root-knot nematode, .

Sugar beet productivity is highly constrained by the root-knot nematode (RKN) . Eight sugar beet genotypes were screened under greenhouse conditions for their susceptibility to according to an adapted quantitative scheme for assignment Canto-Saenz's host suitability (resistance) designations (AQSCS). Besides, the degree of susceptibility or tolerance of the examined genotypes was recorded by the modified host-parasite index (MHPI) scale based on yield performance.

Person Re-Identification Using Deep Modeling of Temporally Correlated Inertial Motion Patterns.

Person re-identification (re-ID) is among the essential components that play an integral role in constituting an automated surveillance environment. Majorly, the problem is tackled using data acquired from vision sensors using appearance-based features, which are strongly dependent on visual cues such as color, texture, etc., consequently limiting the precise re-identification of an individual.

Utilization of High throughput microcrystalline cellulose decorated silver nanoparticles as an eco-nematicide on root-knot nematodes.

The present study aimed to evaluate the influence of high throughput microcrystalline cellulose embedded silver nanoparticles (Ag-NPs), as an alternative eco-nematicide on Root-knot nematode (Meliodogyne incognita), which deem the main reason toward the loss of more than 20% in crops worldwide. In this work, Ag-NPs was prepared in very high concentration. Ag-NPs prepared using such technique has many advantages such as: absence of organic or solvents, scaling up thru using high concentration of silver precursor and utilization of environmentally benign polymer; Microcrystalline Cellulose (MCC).