A novel dataset of date fruit for inspection and classification.

Date fruit grading and inspection is a challenging and crucial process in the industry. The grading process requires skilled and experienced labour. Moreover, the labour turnover in the date processing industries has been increased regularly.

The utilization of date palm waste as an efficient adsorbent for the elimination of heavy metals from polluted water.

This study focuses on the removal of heavy metal ions, such as cadmium (Cd), lead (Pb), chromium (Cr), and zinc (Zn) from water. Metals, which are often present in water, can have various origins, i.e.

A new hybrid algorithm for intelligent detection of sudden decline syndrome of date palm disease.

Date palm is an important domestic cash crop in most countries. Sudden Decline Syndrome (SDS) causes a huge loss to the crop both in quality and quantity. The literature reports the significance of early detection of disease towards preventive measures to improve the quality of the crop.

A novel dataset of guava fruit for grading and classification.

Machine learning algorithms play a vital role in object detection and recognition. Currently, Machine learning techniques have achieved significant performance in various areas. However, there is still a need for research in the agriculture sector.

Adsorption of arsenic (III) from aqueous solution by a novel phosphorus-modified biochar obtained from Taraxacum mongolicum Hand-Mazz: Adsorption behavior and mechanistic analysis.

A novel phosphorus (P) modified biochar (PLBC) was produced by pyrolyzing biomass of the dietic herb Taraxacum mongolicum Hand-Mazz (TMHM) and treating it with monopotassium phosphate (KHPO). This phosphorous loaded biochar was then assessed as adsorbent for As(III) removal from contaminated water. In the current research, the adsorbent was characterized before and after P loading by means of SEM-EDX, TEM, FTIR and XRD techniques.