Fruit Battery with Charging Concept for Oil Palm Maturity Sensor

There are many factors affecting oil extraction rate (OER) but a large contributor to high national OER is by processing good-quality fresh fruit bunches (FFB) at the mills. The current practice for grading oil palm fruit bunches in mills is using human graders for visual inspection, which can lead to repeated mistakes, inconsistent evaluation results, and many other related losses. This study aims to develop a fruit maturity sensor that can detect oil palm fruit maturity grade and send indication to the user whether to accept or reject the bunches. This study focuses on fruit battery principle and applying the charging concept to the fruit battery in order to generate significant load voltage readings of oil palm fruit battery. The charging process resulted in amplified load voltage readings, which were 4 times more sensitive to changes as compared to normal fruit battery without charging process. From the load voltage readings, the fruits can be characterized into their maturity grade based on moisture content. It was determined that fruits with moisture content less than 44% and average load voltage, Vavg, between 20 to 30 mV are considered ripe fruits.

The relation of carcass physiological maturity to meat quality in the Canadian Bison Grading System

López-Campos, Ó., Aalhus, J. L., Galbraith, J., Larsen, I. L., Juárez, M., Uttaro, B. and Robertson, W. M. 2014. The relation of carcass physiological maturity to meat quality in the Canadian Bison Grading System. Can. J. Anim. Sci. 94: 55–62. A total of 119 bull (n=62) and heifer (n=57) bison carcasses were selected to determine the effectiveness of youthful to intermediate physiological maturity [ossification at the 9th/10th/11th thoracic spinous processes (≤50%; 51–65%; 66–80%)] range to accurately classify bison carcasses with respect to quality. Carcasses were classified into three maturity groups according to ossification at the 9th/10th/11th thoracic spinous processes (≤50%; 51–65%; 66–80%). Carcass, meat quality and sensory evaluation data were then collected. Bull carcasses were significantly (P<0.0001) heavier than heifers (308.0 vs. 228.6 kg), while heifers had higher (P<0.0001) marbling scores than bulls (368 vs. 289). For both genders, ossification group had little or no impact (P>0.05) on any of the meat quality traits. Gender had an impact on the shear force values for both fresh (P<0.0001) and frozen/thawed (P=0.0002) samples, with bulls having higher values than heifers. Panellists detected differences between heifers and bulls in initial tenderness (P<0.0001; 7.11 vs. 6.27), flavour intensity (P=0.005; 5.40 vs. 5.14), amount of connective tissue (P=0.0002; 7.64 vs. 7.18), and overall tenderness (P=0.003; 7.13 vs. 6.50). Only initial juiciness was significantly affected (P=0.02) by the ossification group (5.38, 5.64 and 5.76). A gender×ossification group interaction was also detected for flavour intensity (P=0.004) and off-flavour intensity (P=0.03), but the magnitudes of the differences were in the order of one-half panel unit or less, generally below the detection of most consumers. The range of physiological maturity studied had limited effects on meat quality and support the elimination of an intermediate physiological maturity grade (51–80% ossification) from the Canadian Bison Grading System.

Study on the Intelligent Recognition Method for the Maturity Grade of Fresh Corn Ear Based on Computer Vision

In order to realize the intelligent recognition for the maturity grade of fresh corn ear, intelligent inspection system was studied based on computer vision, which could automatically complete the collection and handling of ear graphic and the recognition of maturity of the corn ear. Based on the study, a kind of intelligent recognition method was put forward under the graphic of certain frequency domain. An energy chain was established, and the characters of energy spectrum was extracted through the two-dimensional inverse discrete Fourier transformation on the graphics collected. With the above characters, a probabilistic neural network was developed, the accuracy rate of the recognition method could be 96.7%.

Biometric investigations on the cnidae of the Aegean colour morphs of Anemonia viridis

The sea anemone Anemonia viridis is one of the most common species of the North Aegean Sea. The variety in colour morphs exhibited by this species, causes problems to taxonomy and ecology, and suggests that A. viridis should be subdivided into two distinct species according to the colour of the individuals. The approach used in this study was based on the biometrical cnidae characteristics of the two colour morphs (rustica and smaragdina), as it is known that cnidae biometry has been used as a taxonomic tool for the phylum Cnidaria. More than 20,000 nematocysts were measured to try and find a correlation between these measurements and some body parameters indicative of the maturity grade of the individuals, as potential taxonomic characteristics. Stable cnidae characteristics of the two different colour morphs were compared. However, they differed only in the biometry of the tentacles' a-basitrichs. This slight difference does not support the proposal to subdivide Anemonia viridis into two different species.