An environmentally friendly and cost effective technique for the commercial cultivation of oyster mushroom [Pleurotus florida (Mont.) Singer]

BACKGROUND: The existing protocol for the cultivation of oyster mushroom (Pleurotus florida) in polyethylene bags leads to environmental pollution amounting to 18 g of polyethylene per 450 g of mushroom, which is the average biological efficiency achieved from a bag. Thus the projected annual global pollution amounts to 2 million tones, corresponding to the production of 48 million tones. Experiments were conducted at Kerala Agricultural University, India, to formulate an oyster mushroom cultivation strategy that reduces this pollution level. RESULTS: Pooled results of experiments at the institute's and farmers' units have shown that reusable plastic buckets having perforations of 1.5 cm × 1.0 cm throughout the side walls could be used to substitute polyethylene bags, while following the standard cultivation protocols. Cultivation in perforated buckets has recorded a biological efficiency of 435.69 ± 56.75 g in 47.07 ± 5.22 days against 459.11 ± 53.52 g in 38.05 ± 4.54 days in polyethylene bags. The rate of contamination in buckets was significantly lower than that in bags: 9.28 ± 2.12 and 12.60 ± 3.73% respectively. CONCLUSION: Reusable plastic buckets with perforations on the side walls could be used to substitute the conventional polyethylene bags in oyster mushroom cultivation, with no significant difference in yield. Losses due to slight increase in crop duration in buckets will be compensated with a lower rate of contamination. For a unit having a daily output of 100 kg, it was estimated that during 10 years of permanent cultivation following this technique, the cost of cultivation could be reduced to one‐tenth and the environmental pollution reduced by at least 730 000 non‐degradable polyethylene bags. © 2012 Society of Chemical Industry     

An optimal feature enriched region of interest (ROI) extraction for periocular biometric system

With the onset of COVID-19 pandemic, wearing of face mask became essential and the face occlusion created by the masks deteriorated the performance of the face biometric systems. In this situation, the use of periocular region (region around the eye) as a biometric trait for authentication is gaining attention since it is the most visible region when masks are used. One important issue in periocular biometrics is the identification of an optimal size periocular ROI which contains enough features for authentication. The state of the art ROI extraction algorithms use fixed size rectangular ROI calculated based on some reference points like center of the iris or centre of the eye without considering the shape of the periocular region of an individual. This paper proposes a novel approach to extract optimum size periocular ROIs of two different shapes (polygon and rectangular) by using five reference points (inner and outer canthus points, two end points and the midpoint of eyebrow) in order to accommodate the complete shape of the periocular region of an individual. The performance analysis on UBIPr database using CNN models validated the fact that both the proposed ROIs contain enough information to identify a person wearing face mask.