This paper aims to study a triple flat-type air coil inductive sensor that can identify two maturity stages of oil palm fruits, ripe and unripe, based on the resonance frequency and fruitlet capacitance changes. There are two types of triple structure that have been tested, namely Triple I and II. Triple I is a triple series coil with a fixed number of turns (n = 200) with different length, and Triple II is a coil with fixed length (l = 5 mm) and a different number of turns. The peak comparison between Triple I and II is using the coefficient of variation cv, which is defined as the ratio of the standard deviation to the mean to express the precision and repeatability of data. As the fruit ripens, the resonance frequency peaks from an inductance⁻frequency curve and shifts closer to the peak curve of the air, and the fruitlet capacitance decreases. The coefficient of the variation of the inductive oil palm fruit sensor shows that Triple I is smaller and more consistent in comparison with Triple II, for both resonance frequency and fruitlet capacitance. The development of this sensor proves the capability of an inductive element such as a coil, to be used as a sensor so as to determine the ripeness of the oil palm fresh fruit bunch sample.
A recently developed rapid co-composting of oil palm empty fruit bunch (OPEFB) and palm oil mill effluent (POME) anaerobic sludge is beginning to attract attention from the palm oil industry in managing the disposal of these wastes. However, a deeper understanding of microbial diversity is required for the sustainable practice of the co-compositing process. In this study, an in-depth assessment of bacterial community succession at different stages of the pilot scale co-composting of OPEFB-POME anaerobic sludge was performed using 454-pyrosequencing, which was then correlated with the changes of physicochemical properties including temperature, oxygen level and moisture content. Approximately 58,122 of 16S rRNA gene amplicons with more than 500 operational taxonomy units (OTUs) were obtained. Alpha diversity and principal component analysis (PCoA) indicated that bacterial diversity and distributions were most influenced by the physicochemical properties of the co-composting stages, which showed remarkable shifts of dominant species throughout the process. Species related to Devosia yakushimensis and Desemzia incerta are shown to emerge as dominant bacteria in the thermophilic stage, while Planococcus rifietoensis correlated best with the later stage of co-composting. This study proved the bacterial community shifts in the co-composting stages corresponded with the changes of the physicochemical properties, and may, therefore, be useful in monitoring the progress of co-composting and compost maturity.
Oil palm ripeness' main evaluation procedure is traditionally accomplished by human vision. However, the dependency on human evaluators to grade the ripeness of oil palm fresh fruit bunches (FFBs) by traditional means could lead to inaccuracy that can cause a reduction in oil palm fruit oil extraction rate (OER). This paper emphasizes the fruit battery method to distinguish oil palm fruit FFB ripeness stages by determining the value of load resistance voltage and its moisture content resolution. In addition, computer vision using a color feature is tested on the same samples to compare the accuracy score using support vector machine (SVM). The accuracy score results of the fruit battery, computer vision, and a combination of both methods' accuracy scores are evaluated and compared. When the ripe and unripe samples were tested for load resistance voltage ranging from 10 Ω to 10 kΩ, three resistance values were shortlisted and tested for moisture content resolution evaluation. A 1 kΩ load resistance showed the best moisture content resolution, and the results were used for accuracy score evaluation comparison with computer vision. From the results obtained, the accuracy scores for the combination method are the highest, followed by the fruit battery and computer vision methods.
As the main exporter in the oil palm industry, the need to improve the quality of palm oil has become the main interest among all the palm oil millers in Malaysia. To produce good quality palm oil, it is important for the miller to harvest a good oil palm Fresh Fruit Bunch (FFB). Conventionally, the main reference used by Malaysian harvesters is the manual grading standard published by the Malaysian Palm Oil Board (MPOB). A good oil palm FFB consists of all matured fruitlets, aged between 18 to 21 weeks of antheses (WAA). To expedite the harvesting process, it is crucial to implement an automated detection system for determining the maturity of the oil palm FFB. Various automated detection methods have been proposed by researchers in the field to replace the conventional method. In our preliminary study, a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunch was proposed. The design of the proposed air coil sensor based on the inductive sensor was further investigated mainly in the context of the effect of coil diameter to improve its sensitivity. In this paper, the sensitivity of the inductive sensor was further examined with a dual flat-type shape of air coil. The dual air coils were tested on fifteen samples of fruitlet from two categories, namely ripe and unripe. Samples were tested within 20 Hz to 10 MHz while evaluations on both peaks were done separately before the gap between peaks was analyzed. A comparative analysis was conducted to investigate the improvement in sensitivity of the induction-based oil palm fruit sensor as compared to previous works. Results from the comparative study proved that the inductive sensor using a dual flat-type shape air coil has improved by up to 167%. This provides an indication in the improvement in the coil sensitivity of the palm oil fruit sensor based on the induction concept.
Among palm oil millers, the ripeness of oil palm Fresh Fruit Bunch (FFB) is determined through visual inspection. To increase the productivity of the millers, many researchers have proposed with a new detection method to replace the conventional one. The sensitivity of such a sensor plays a crucial role in determining the effectiveness of the method. In our preliminary study a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunches is proposed. The design of the proposed air coil sensor based on an inductive sensor is further investigated to improve its sensitivity. This paper investigates the results pertaining to the effects of the air coil structure of an oil palm fruit sensor, taking consideration of the used copper wire diameter ranging from 0.10 mm to 0.18 mm with 60 turns. The flat-type shape of air coil was used on twenty samples of fruitlets from two categories, namely ripe and unripe. Samples are tested with frequencies ranging from 20 Hz to 120 MHz. The sensitivity of the sensor between air to fruitlet samples increases as the coil diameter increases. As for the sensitivity differences between ripe and unripe samples, the 5 mm air coil length with the 0.12 mm coil diameter provides the highest percentage difference between samples and it is amongst the highest deviation value between samples. The result from this study is important to improve the sensitivity of the inductive oil palm fruit sensor mainly with regards to the design of the air coil structure. The efficiency of the sensor to determine the maturity of the oil palm FFB and the ripening process of the fruitlet could further be enhanced.
From the Malaysian harvester's perspective, the determination of the ripeness of the oil palm (FFB) is a critical factor to maximize palm oil production. A preliminary study of a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunches is presented. To optimize the functionality of the sensor, the frequency characteristics of air coils of various diameters are investigated to determine their inductance and resonant characteristics. Sixteen samples from two categories, namely ripe oil palm fruitlets and unripe oil palm fruitlets, are tested from 100 Hz up to 100 MHz frequency. The results showed the inductance and resonant characteristics of the air coil sensors display significant changes among the samples of each category. The investigations on the frequency characteristics of the sensor air coils are studied to observe the effect of variations in the coil diameter. The effect of coil diameter yields a significant 0.02643 MHz difference between unripe samples to air and 0.01084 MHz for ripe samples to air. The designed sensor exhibits significant potential in determining the maturity of oil palm fruits.
This study adopts the pyrosequencing technique to identify bacteria present on 26 kitchen cutting boards collected from different grades of food premises around Seri Kembangan, a city in Malaysia. Pyrosequencing generated 452,401 of total reads of OTUs with an average of 1.4×10(7) bacterial cells/cm(2). Proteobacteria, Firmicutes and Bacteroides were identified as the most abundant phyla in the samples. Taxonomic richness was generally high with >1000 operational taxonomic units (OTUs) observed across all samples. The highest appearance frequencies (100%) were OTUs closely related to Enterobacter sp., Enterobacter aerogenes, Pseudomonas sp. and Pseudomonas putida. Several OTUs were identified most closely related to known food-borne pathogens, including Bacillus cereus, Cronobacter sakazaki, Cronobacter turisensis, Escherichia coli, E. coli O157:H7, Hafnia alvei, Kurthia gibsonii, Salmonella bongori, Salmonella enterica, Salmonella paratyphi, Salmonella tyhpi, Salmonella typhimurium and Yersinia enterocolitica ranging from 0.005% to 0.68% relative abundance. The condition and grade of the food premises on a three point cleanliness scale did not correlate with the bacterial abundance and type. Regardless of the status and grades, all food premises have the same likelihood to introduce food-borne bacteria from cutting boards to their foods and must always prioritize the correct food handling procedure in order to avoid unwanted outbreak of food-borne illnesses.
Primary open angle glaucoma (POAG), a major cause of blindness worldwide, is a complex disease with a significant genetic contribution. We performed Exome Array (Illumina) analysis on 3504 POAG cases and 9746 controls with replication of the most significant findings in 9173 POAG cases and 26 780 controls across 18 collections of Asian, African and European descent. Apart from confirming strong evidence of association at CDKN2B-AS1 (rs2157719 [G], odds ratio [OR] = 0.71, P = 2.81 × 10(-33)), we observed one SNP showing significant association to POAG (CDC7-TGFBR3 rs1192415, ORG-allele = 1.13, Pmeta = 1.60 × 10(-8)). This particular SNP has previously been shown to be strongly associated with optic disc area and vertical cup-to-disc ratio, which are regarded as glaucoma-related quantitative traits. Our study now extends this by directly implicating it in POAG disease pathogenesis.
Primary angle closure glaucoma (PACG) is a major cause of blindness worldwide. We conducted a genome-wide association study (GWAS) followed by replication in a combined total of 10,503 PACG cases and 29,567 controls drawn from 24 countries across Asia, Australia, Europe, North America, and South America. We observed significant evidence of disease association at five new genetic loci upon meta-analysis of all patient collections. These loci are at EPDR1 rs3816415 (odds ratio (OR) = 1.24, P = 5.94 × 10(-15)), CHAT rs1258267 (OR = 1.22, P = 2.85 × 10(-16)), GLIS3 rs736893 (OR = 1.18, P = 1.43 × 10(-14)), FERMT2 rs7494379 (OR = 1.14, P = 3.43 × 10(-11)), and DPM2-FAM102A rs3739821 (OR = 1.15, P = 8.32 × 10(-12)). We also confirmed significant association at three previously described loci (P < 5 × 10(-8) for each sentinel SNP at PLEKHA7, COL11A1, and PCMTD1-ST18), providing new insights into the biology of PACG.