Measured Quality Parameters Research Articles

Factors Associated with Legionella Detection in the Water Systems of National Lodging Organization Facilities with Water Management Programs in the United States.

A better understanding of risk factors and the predictive capability of water management program (WMP) data in detecting Legionella are needed to inform the efforts aimed at reducing Legionella growth and preventing outbreaks of Legionnaires' disease. Using WMPs and Legionella testing data from a national lodging organization in the United States, we aimed to (1) identify factors associated with Legionella detection and (2) assess the ability of WMP disinfectant and temperature metrics to predict Legionella detection. We conducted a logistic regression analysis to identify WMP metrics associated with Legionella serogroup 1 (SG1) detection. We also estimated the predictive values for each of the WMP metrics and SG1 detection. Of 5435 testing observations from 2018 to 2020, 411 (7.6%) had SG1 detection, and 1606 (29.5%) had either SG1 or non-SG1 detection. We found failures in commonly collected WMP metrics, particularly at the primary test point for total disinfectant levels in hot water, to be associated with SG1 detection. These findings highlight that establishing and regularly monitoring water quality parameters for WMPs may be important for preventing Legionella growth and subsequent disease. However, while unsuitable water quality parameter results are associated with Legionella detection, this study found that they had poor predictive value, due in part to the low prevalence of SG1 detection in this dataset. These findings suggest that Legionella testing provides critical information to validate if a WMP is working, which cannot be obtained through water quality parameter measurements alone.

How to investigate differences in indoor environmental comfort and adaptation? Mixed methods research with patients

ABSTRACT Ensuring hospitalized patients’ comfort requires understanding differences in comfort and adaptation to discomfort, as well as the role of the built environment therein. Shortcomings in this understanding result from limitations of existing research methods. Therefore the potential of a mixed methods research design to investigate when and why experiences of and adaption to (dis)comfort differ among hospitalized patients was explored. A convergent mixed methods case study was conducted in two hospital wards of a Belgian hospital. Qualitative data included interviews with 19 patients about their experiences and information about the patients at the two wards during the fieldwork; quantitative data included sensor measurements of indoor environmental quality parameters (i.e. illuminance and indoor temperature), a questionnaire among 238 patients about their assessment of the indoor conditions, and simulations of these conditions. Joint displays allowed comparing situations in which characteristics related to the patients or their setting differed in an integrated way. The displays provide an intermediate step between purely qualitative descriptions of comfort and adaptation and purely quantitative models that predict both. Scenarios that the joint displays allow identifying inform about characteristics that could improve these models, and about roles of the built environment in experiences.

Comparing performance, morphological, physical, and chemical properties of eggs produced by 1940 Leghorn or a commercial 2016 Leghorn fed representative diets from 1940 to 2016

Eggshell quality is one of the most significant factors affecting the egg industry as it economically influences the quantity of saleable eggs. Eggshell quality can be improved through optimization of genotype, housing system, and mineral nutrition. This study aimed to compare genotypes and evaluate the morphological, physical, and chemical properties of eggs (weight, breaking strength, Haugh units, and dry matter) by hens of two different strains fed a 1940 and 2016 representative diet. Egg production was measured daily and there were four periods with 10-wk intervals in which eggs were analyzed starting at 30 wk and ending at 60 wk of age measuring quality parameters. This study was set as a 2 × 2 factorial. The factors consisted of 2 leghorn genetic strains that were a 2016 commercial layer (W36) and a 1940 random-bred leghorn line, then 2 diets based on 2016 and 1940 dietary standards. The treatment groups: 1) 2016 hen on 1940 diet, 2) 2016 hen on 2016 diet, 3) 1940 hen on 1940 diet, and 4) 1940 hen on 2016 diet had 8 replicates with 10 hens per treatment housing 2 hens per cage. Body weights were higher in the 2016 hens when compared to the 1940 hens, however, the feed conversion ratio fluctuated in hens with the 2016 hens on the 1940 diet consuming the most feed throughout the majority of the trial. The 1940s hens came into production later than the 2016 hens; however, the rate of production was consistent with one another. Oviduct and ovary weights were heavier in the 2016 hens when compared to the 1940 hens. Egg quality, both interior and exterior was greater in the 2016 hens when compared to the 1940 hens. Parameters measured demonstrated significant differences (P ≤ 0.05) among treatment groups suggesting that genetics and nutrition both played a role in production rate and egg quality.

Soybean root image dataset and its deep learning application for nodule segmentation

The root is very important for anchoring the plant and acquiring water and nutrients from the soil for growth. Plant root trait phenotyping using imaging (2D and 3D) techniques is gaining importance in agriculture to enhance the breeding of superior cultivars. However, most root image data have been collected under controlled growth conditions, such as in greenhouses and growth chambers. In this study, we propose collecting soybean root image datasets from open field conditions for root phenotyping. There are numerous methods for segmenting images, but many of them are not suitable for the tiny and nodulated architecture of root. Advancements such as deep learning (DL) methods and semantic segmentation algorithms have been actively applied in many research studies. In the current study, we used convolutional neural network (CNN) based U-Net with six convolution methods and Deeplabv3+ and compared their performance in nodule identification based on the Dice coefficient, GPU memory usage, qualitative image segmentation, training time, and inference time. Also, we employed two image processing, resizing and patching, for efficient training of images with very high resolution. The results indicated accurate segmentation of root nodules; in addition, the results for the segmentation of root nodules using DL high-resolution (HR) images were more precise and efficient than those with low-resolution (LR) images since the Dice coefficient value and rate of nodule size were high in HR images although the former required more training time and higher GPU memory. Furthermore, in comparison to the resizing approach, patch-based approach outperformed in all aspects of performance. Among the DL models that we employed for our study, the grouped convolution-based U-net showed the best results having high Dice coefficient values 0.647 and 0.618 for 600x400 and 300x200 images respectively in resizing approach and dynamic convolution-based U-net showed the best results having Dice coefficient values 0.792 and 0.777 for 600x400 and 300x200 patch images respectively in patch-based approach. Thus, the optimized DL model presented in this study has the potential to be a valuable tool for the automated analysis of soybean root systems, assisting in the measurement of various root quality parameters and contributing to the development of superior cultivars.

Suspected Legionella Transmission from a Single Donor to Two Lung Transplant Recipients — Pennsylvania, May 2022

In July 2022, the Pennsylvania Department of Health received two reports of laboratory-confirmed Legionnaires disease in patients who had recently received lung transplants from the same donor at a single Pennsylvania hospital. The donor’s cause of death was freshwater drowning in a river, raising suspicion of potential donor-derived transmission, because Legionella bacteria naturally live in fresh water. Further investigation of patients receiving other organs from the same donor did not identify additional legionellosis cases. Health care–associated infection caused by water exposure at the hospital was also evaluated as a potential source of infection and was found to be unlikely. Hospital water quality parameter measurements collected during May–June 2022 were within expected ranges and no water disruptions were noted, although no testing for Legionella was performed during this period. Notifiable disease data did not identify any other Legionnaires disease cases with exposure to this hospital within the 6 months before or after the two cases. Although laboratory testing did not confirm the source of recipient infections, available data suggest that the most likely source was the donor lungs. This cluster highlights the need for increased clinical awareness of possible infection with Legionella in recipients of lungs from donors who drowned in fresh water before organ recovery.

Effects of Milking System Operating Conditions on the Milk-Fat-Percentage Measuring Accuracy of an Inline Light-Scattering Sensor

Contamination of the inner surface of milk hoses of milking systems with milk residues, water residues and pathogenic microflora has a negative impact on milk quality and can affect the accuracy of light-scattering sensors measuring milk quality parameters. A three-stage study of the influence of milking system operating conditions on the accuracy of a light-scattering sensor is presented. The growth of pathogenic microflora on the inner surface of milk hoses was studied, the flow of milk and milk hoses rinsing was simulated and the accuracy of the light-scattering sensor was tested under conditions of low-quality rinsing of the milking system. A significant difference in the total microbial count was detected between the milk residues of healthy animals and the milk residues of animals with subclinical mastitis (1.2 × 104 CFU/mL and 9.2 × 104 CFU/mL). The presence of Staphylococcus (aureus and epidermidis) was detected in quantities much lower than those that could interfere with the analysis of milk quality parameters. Simulation modeling allowed us to prove that even when rinsing with hot water (80 °C) without chemical solutions, pathogenic microflora in milk hoses of the milking system will be suppressed. Modeling of the milk flow in the measuring chamber of the device showed the stable replacement of milk in the measuring chamber and provided actual measurements of milk quality parameters. It has been determined that low-quality rinsing and water residues in milk hoses lead to a significant increase in measurement error up to 15–20% during the first 30–40 s after the milking system starts operating. The study results confirm that the light-scattering sensors are resistant to such factors of the milking system operation as contamination by pathogenic microflora (S. aureus and S. epidermidis) and low-quality rinsing of milk hoses.

PHYSICAL WATER QUALITY PARAMETERS IN BOYO RIVER ONOWAEMBO VILLAGE, GUNUNGSITOLI SUBDISTRICT, GUNUNGSITOLI CITY

Water is a natural resource needed for many people’s livelihood. Clean water quality would affect the health of the environment and all activities beyond. This research was conducted on October 28th 2022 in Boyo River. The purpose of this study was to figure out the measurement of physical quality parameters and to determine the condition of Boyo River. Observations of physical water quality parameters were carried out at 3 location points through observation method. Data from measurements of current speed, depth, sunlight penetration, bottom substrate, river width, water color and odor were analyzed descriptively. The research result showed that the Boyo River in Onowaembo Village had not been polluted in accordance with PP No. 82 of 2001.

Generation of femtosecond pulses with an energy of ~10 μJ at a wavelength of 1.56 μM and nonlinear conversion of their frequency in a hollow revolver fiber

A fiber source of ultrashort pulses (USPs) with a powerful hybrid amplifier based on erbium and erbium-ytterbium fibers connected in series with a double cladding and an increased mode diameter, pumped by multimode laser diodes at a wavelength of 976 nm, was created and studied. Pulses from the output of a powerful amplifier at a central wavelength of about 1.56 μm with a duration of ~200 ps and an energy of up to 21.9 μJ, following with a frequency of 198.5 kHz, were compressed using a compressor based on a pair of volumetric polarization-independent diffraction gratings operating at transmission, with an efficiency of ≈73%. A minimum duration of compressed pulses of 742 fs was achieved, while their maximum energy and peak power were 15.8 μJ and ≈13 MW, respectively (maximum average power - 3.14 W) at a central wavelength of 1.56 μm in a beam with a Gaussian profile and measured quality parameters = 1.58 and = 1.38. When pumped by pulses from an erbium fiber source of various durations, the SRS transformation of 1.56 μm → 1.71 μm was realized in a hollow revolver light guide with a core of 75 μm in diameter filled with molecular hydrogen. Pulses with a maximum energy of about 200 nJ at a wavelength of 1.71 μm were obtained. The developed ultrashort pulse source can be useful in creating advanced systems for precision processing of transparent materials, especially silicon, as well as for other applications that require high energy and peak power of ultrashort pulses.

Suspected Legionella Transmission from a Single Donor to Two Lung Transplant Recipients - Pennsylvania, May 2022.

In July 2022, the Pennsylvania Department of Health received two reports of laboratory-confirmed Legionnaires disease in patients who had recently received lung transplants from the same donor at a single Pennsylvania hospital. The donor's cause of death was freshwater drowning in a river, raising suspicion of potential donor-derived transmission, because Legionella bacteria naturally live in fresh water. Further investigation of patients receiving other organs from the same donor did not identify additional legionellosis cases. Health care-associated infection caused by water exposure at the hospital was also evaluated as a potential source of infection and was found to be unlikely. Hospital water quality parameter measurements collected during May-June 2022 were within expected ranges and no water disruptions were noted, although no testing for Legionella was performed during this period. Notifiable disease data did not identify any other Legionnaires disease cases with exposure to this hospital within the 6 months before or after the two cases. Although laboratory testing did not confirm the source of recipient infections, available data suggest that the most likely source was the donor lungs. This cluster highlights the need for increased clinical awareness of possible infection with Legionella in recipients of lungs from donors who drowned in fresh water before organ recovery.

FT-NIR as a technique for objective measurement of film quality parameters

FT-NIR as a technique for objective measurement of film quality parameters

Air Quality Study in Mijen District, Semarang City in 2022

The higher the air pollution in an area, the more it can have a negative impact on human health status if inhaled continuously, especially in the respiratory system. This study used secondary data obtained from the Environment and Forestry Service. The data was analyzed using a descriptive method by comparing data collected in the field with ambient air quality standards based on Government Regulation Number 22 of 2021 concerning the Implementation of Environmental Protection and Management to determine air quality conditions in Mijen District, Semarang City. The impact resulting from air pollution can interfere with the health of living things and damage the ecosystem environment. Human health will be disrupted due to polluted air, which can lead to diseases such as ARI, heart disease, and even lung cancer, which is very dangerous. For this reason, it is necessary to conduct research on air quality to prevent air pollution that exceeds ambient air quality standards, which can cause health problems for the community in Mijen District. Based on research on the analysis of air quality parameter measurement results in Mijen District, Semarang City, it can be concluded that all air quality parameters do not exceed quality standards.

Study of Water Quality and Heavy Metals in Several Locations in Rivers and Estuaries of Lurang Village, North Wetar, Southwest Maluku, Indonesia

Water plays an important role in life and is a vital component that supports biodiversity and secures the existence of ecosystems. Water sampling in this study consisted of 13 stations, namely 10 stations in river waters and 3 stations in estuary areas in the waters of Lurang Village, North Wetar District, Southwest Maluku Regency, Indonesia. The water quality parameter measurement results show that the water quality conditions in several locations are below the optimum limit. Heavy metal test samples were taken from 4 locations, namely RW35, RW36, RW39 and RWBG.Ds to be tested for the metal content of Selenium (Se), Cadmium (Cd), Copper (Cu), Lead (Pb) and Mercury (Hg). The presence of heavy metals in waters is a result of pollution from industrial, agricultural and other waste products. This study aims to determine the water quality and distribution of heavy metals in the river and estuary waters in Lurang Village, North Wetar District, West Maluku Regency.

Mitigation of High Solar Irradiance and Heat Stress in Kiwifruit during Summer via the Use of Alleviating Products with Different Modes of Action—Part 2 Effects on Fruit Quality, Organoleptic, and Phytochemical Properties at Harvest and after Storage

In Greece, kiwifruit is grown in areas characterized by high temperatures during the summer months, with high solar radiation, especially during the period of shoot growth and fruit maturation. Therefore, the impact of heat stress is crucial. The objective of the present study was to evaluate the effect of pre-harvest alleviating products’ application in the field on the yield and fruit quality attributes of ‘Hayward’ kiwifruit before and after storage. To achieve this, the osmoprotectant BlueStim (glycine betaine), the reflectant Purshade (calcium carbonate 62.5% w/w), and the antioxidant Sun Protect were applied by foliar spraying. Fruits produced under the influence of BlueStim exhibited high soluble sugars, total phenols, total flavanols, total flavonoids, and FRAP antioxidant capacity at harvest, while the production per vine increased by almost 17% compared to control. After storage, fruits produced from vines pre-harvest treated with BlueStim showed increased concentrations of soluble sugars, ascorbic acid, total organic acids, total flavonoids, and antioxidant capacity. Fruits produced from vines treated with Purshade presented high concentrations of soluble sugars, total phenols, FRAP and DPPH antioxidant capacity, total soluble solids, and malic acid, while Sun Protect application resulted in increased fruit firmness and total phenols as well. Therefore, the applied treatments alleviated, to some extent, the negative impact of heat stress on fruit quality, with variable effects on the measured quality parameters.

Impact of supplementary air filtration on aerosols and particulate matter in a UK hospital ward: a case study

Aerosol spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a major problem in hospitals, leading to an increase in supplementary high-efficiency particulate air filtration aimed at reducing nosocomial transmission. This article reports a natural experiment that occurred when an air cleaning unit (ACU) on a medicine for older people ward was switched off accidentally while being commissioned. To assess aerosol transport within the ward and determine whether the ACU reduced airborne particulate matter (PM) levels. An ACU was placed in a ward comprising two six-bedded bays plus three single-bed isolation rooms which had previously experienced several outbreaks of coronavirus disease 2019. During commissioning, real-time measurements of key indoor air quality parameters (PM1-10, CO2, temperature and humidity) were collected from multiple sensors over 2 days. During this period, the ACU was switched off accidentally for approximately 7h, allowing the impact of the intervention on PM to be assessed. The ACU reduced the PM counts considerably (e.g. PM1 65.5-78.2%) throughout the ward (P<0.001 all sizes), with positive correlation found for all PM fractions and CO2 (r=0.343-0.817; all P<0.001). PM counts rose/fell simultaneously when the ACU was off, with correlation of PM signals from multiple locations (e.g. r=0.343-0.868; all P<0.001) for particulates <1μm). Aerosols migrated rapidly between the various ward subcompartments, suggesting that social distancing alone cannot prevent nosocomial transmission of SARS-CoV-2 as this fails to mitigate longer-range (>2m) transmission. The ACU reduced PM levels considerably throughout the ward space, indicating its potential as an effective intervention to reduce the risk posed by infectious airborne particles.

A Systematic Review of Real-Time Monitoring Technologies and Its Potential Application to Reduce Food Loss and Waste: Key Elements of Food Supply Chains and IoT Technologies

Continuous monitoring of food loss and waste (FLW) is crucial for improving food security and mitigating climate change. By measuring quality parameters such as temperature and humidity, real-time sensors are technologies that can continuously monitor the quality of food and thereby help reduce FLW. While there is enough literature on sensors, there is still a lack of understanding on how, where and to what extent these sensors have been applied to monitor FLW. In this paper, a systematic review of 59 published studies focused on sensor technologies to reduce food waste in food supply chains was performed with a view to synthesising the experience and lessons learnt. This review examines two aspects of the field, namely, the type of IoT technologies applied and the characteristics of the supply chains in which it has been deployed. Supply chain characteristics according to the type of product, supply chain stage, and region were examined, while sensor technology explores the monitored parameters, communication protocols, data storage, and application layers. This article shows that, while due to their high perishability and short shelf lives, monitoring fruit and vegetables using a combination of temperature and humidity sensors is the most recurring goal of the research, there are many other applications and technologies being explored in the research space for the reduction of food waste. In addition, it was demonstrated that there is huge potential in the field, and that IoT technologies should be continually explored and applied to improve food production, management, transportation, and storage to support the cause of reducing FLW.

STUDY THE EFFECT OF STRAIN MEASURES OF POST-RESUSCITATE AGING AND AGE AT SLAUGHTER ON BROILER MEAT QULITY

The purpose of this study was to investigate the relationships between broiler strain, slaughter age, and post-chill (PC) aging duration in terms of measurable meat quality parameters. Two hundred fifty Hubbard on one day old chicks classic and two hundred fifty Lohman were bread in a commercial setting. Each strain had half of its broiler chicks slain at 32 days of age and the other half at 42 days of age. A total of 168 bodies (84 Hubbard and 84 Lohman) were selected at random on each day of processing, with each strain being divided into 28 groups and aged for 0, 4, and 24 hours. Each strain had a comparable average weekly body weight. Hubbard strain animals demonstrated greater feed conversion ratios during weeks two and three of life (P≥ 0.05). A bird's age had a significant effect (p≥0.05) on initial pH of the carcass, with birds that were 32 days old having lower pH values (41 days old). Carcass temperature of Lohman’s was higher than Hubbard's at 0h, 2h, and 4h post-PC (p≥0.001). Breast temperature was lower in younger birds throughout all PC assessment intervals (p≥0.001). Stress, age, and aging time had no effect on thaw loss, cook loss, and water holding capacity. Meat of Lohman strain was softer (P≥0.05) than meat of Hubbard strain, and as broiler age and aging time rose, softness also improved. The Hubbard strain produced meat was lighter in color and less red than that of Lohman strain, which came from birds of that darker. It was determined that the breast meat quality features were most affected by strain, slaughter age and PC aging period and that softer fillet could be achieved by maturing for 4 hours before to deboning.

Heavy Metals, Pesticide, Plasticizers Contamination and Risk Analysis of Drinking Water Quality in the Newly Developed Housing Societies of Gujranwala, Pakistan

The supply of clean drinking water is essential for a healthy life, but access to safe and healthy drinking water has become a key issue worldwide, especially in developing nations such as Pakistan. This research work focused on investigating the suitability of groundwater by measuring quality parameters, identification of pesticide pollutants, and health risk analysis in adults and children due to the consumption of groundwater in recently developed housing societies of the Gujranwala district, Punjab, Pakistan. Drinking water samples (n = 200) were collected from electric water pumps and analyzed by in situ testings following the Standard American Public Health Association (APHA) methods. Pesticides and plasticizers detection was carried out using gas chromatography-mass spectrometry (GC/MS). Results showed that the concentrations of dissolved Cr and Pb at more than 20% of sampling sites exceeded the allowable limit of the World Health Organization (WHO). However, the measured physico-chemical attributes and concentrations of Fe and Zn did not exceed their respective permissible limits. The most abundant pollutants detected were plasticizers (30); followed by herbicides (21); fungicides, acaricides, and insecticides (16); and various types of plant growth regulators (7). Differential patterns for the hazard quotient (HQ) and hazard indices (HI) were observed, of which were above the WHO limits. The decreasing order of the hazard quotient was Cl &gt; Zn &gt; Mg &gt; Cr &gt; Pb for both adults and children. In crux, the quality of water is poor for drinking purposes and the safety and well-being of residents in the recently developed housing societies of the study area may be at risk. Hence, it is important to implement a plan for water quality management, and the regular monitoring (periodic testing of qualitative and quantitative attributes) of the water quality to overcome health-related issues.

Non-Destructive Measurement of Quality Parameters of Apple Fruit by Using Visible/Near-Infrared Spectroscopy and Multivariate Regression Analysis

The quality assessment and grading of agricultural products is one of the post-harvest activities that has received considerable attention due to the growing demand for healthy and better-quality products. Recently, various non-destructive methods have been used to evaluate the quality of agricultural products, which are very desirable and faster and more economical than destructive methods. Optical methods are one of the most important non-destructive methods that use the high speed of light detection and computer data processing and are able to evaluate the quality and classification of products with high accuracy. Among the optical methods, visible–near-infrared (Vis/NIR) spectroscopy is considered one of the most accurate methods. In this research, Vis/NIR spectroscopy technology was used in the spectral range of 350–1150 nm for non-destructive detection of some quality parameters including pH, TA, SSC, and TP of two varieties of Red Delicious and Golden Delicious apples. Various pre-processing models were developed to predict the parameters, which brought the desired results with high accuracy so that pH prediction results were for yellow apples (RMSEC = 0.009, rc = 0.991, SDR = 2.51) and for red apples (RMSEC = 0.005, rc = 0.998, SDR = 2.56). The results for TA were also (RMSEC = 0.003, rc = 0.996, SDR = 2.51) for red apples and (RMSEC = 0.001, rc = 0.998, SDR = 2.81) for yellow apples. The results regarding SSC were for red apples (RMSEC = 0.209, rc = 0.990 and SDR = 2.82) and for yellow apples (RMSEC = 0.054, SDR = 2.67 and rc = 0.999). In addition, regarding TP, the results were for red apples (RMSEC = 0.2, rc = 0.989, SDR = 2.05) and for yellow apples (RMSEC = 1.457, rc = 0.998, SDR = 1.61). The obtained results indicate the detection of the mentioned parameters with high accuracy by visible/infrared spectroscopic technology.

Predicting single kernel and bulk milled rice alkali spreading value and gelatinization temperature class using NIR spectroscopy

AbstractBackground and ObjectivesThe alkali spreading value (ASV) of rice is a widely measured quality parameter and accepted indicator of gelatinization temperature (GT) class. However, the alkali test, developed in 1958, is labor intensive and subjective. Better methods to measure ASV and GT, for single kernel and bulk rice would provide an important tool to determine the effects of individual kernels on end‐use quality and rice with desired cooking qualities. An instrument developed by the USDA‐ARS and a commercially available near infrared (NIR) instrument were evaluated for determining ASV and classification of intermediate and low GT levels for single kernel and bulk milled rice, respectively.FindingsQuantitative prediction of ASV scores (2–7) demonstrated the potential of NIR spectroscopy for screening with a standard error of prediction for validation samples ranging from 0.91 to 1.39 for the single kernel NIR instrument, and from 0.97 to 1.19 for the commercial instrument. GT categorization into intermediate and low values, using ASV scores, showed 82.4% and 85.0% correct classification using 1 and 30‐single kernel average calibration models, respectively. GT was correctly classified (93.6%–84.4%) using a commercial NIR instrument.ConclusionNIR spectroscopy has potential for rough screening of ASV and for two‐category GT rice classification.Significance and NoveltyConsidering that NIR spectroscopy has been proven to be applicable for other quality parameters, such as rice starch content and quality, protein content, and milling degree, the addition of calibrations for ASV as a predictor of GT class will be highly beneficial while not requiring additional resources. The rapid and nondestructive classification of individual kernels may also enable physical segregation of individual kernels for use by rice researchers and/or industry for additional studies on kernels with specific quality parameters and for determining the extent of variant kernels in a milled rice lot that could affect end use quality. Future studies on the use of NIR spectroscopy for brown rice should be evaluated so that quality could be assessed, while maintaining seed viability, and then used in field studies.

Physical and Mechanical Properties of Coffee Cherries and Beans in Africa: Review and the State of Arts

Coffee is an important source of income for African smallholder farmers. The world is predominated by three coffee varieties, namely Arabica, Robusta, and Liberica originated in the African countries. However, the low coffee quality attributes can affect the coffee beans' price due to the improper post-harvesting processes. Therefore, this work is aimed to review the physical and mechanical properties of the African coffee cherries and beans on the country-wise level, and review the methods used to measure quality parameters and compare the key coffee quality parameters. This work was qualitatively conducted using secondary data on African Arabica and Robusta coffee from journals, conference proceedings, and reports. Methods used for determining the coffee beans' properties were explored country wise. The coffee attributes of the two coffee varieties were compared through statistical analysis using ANOVA. The review found that the coffee quality depends on geographical characteristics, agronomic factors, and post-harvesting processes. The coffee cherries de-pulping process is linked to the coffee quality to avoid the damage of parchment coffee beans based particularly on the size and shape of coffee cherries and beans. The analysed quality parameters showed that the Ethiopian Arabica coffee beans were larger than the Ghanaian Robusta coffee beans. While the size of Robusta coffee in Eastern African countries, particularly Uganda, is bigger than those in Western countries, especially Ghana. Therefore, the information on the coffee quality attributes can help to improve the performance parameters of the coffee de-pulping machine and enhance the price of African coffee.