Characterization of Particle Shape with an Improved 3D Light Scattering Sensor (3D-LSS) for Aerosols.

To characterize fine particulate products in industrial gas-solid processes, insights into the particle properties are accessible via various measurement techniques. For micron particles, online imaging techniques offer a fast and reliable assessment of their size and shape. However, for the shape analysis of submicron particles, only offline techniques, such as SEM and TEM imaging, are available. In this work, an online sensor system based on the principle of elastic light scattering of particles in the gas phase is developed to measure the shape factor of non-spherical particles in the size range of 500 nm to 5 µm. Single aerosol particles are guided through a monochromatic circularly polarized laser light beam by an aerodynamic focusing nozzle, which was developed based on the CFD simulation of the flow and particle movement. The intensity of the scattered light is measured at several discrete positions in the azimuthal direction around the particles. An algorithm computes the sphericity of the particles based on the distribution of the intensity signals. The sensor construction, data processing and analysis are described. Model aerosols with particles of different shapes are investigated to test the developed sensor and show its performance in the determination of the sphericity distribution of particles.

Online Measurement Method and System of Excitation Impedance of Current Transformers Based on Norton's Theorem and Differential Method to Measure Difference of Two Currents.

An online measurement method is proposed in this paper, and a system is established for detecting the excitation impedance of current transformers (CTs) based on Norton's theorem. The theorem is carried out by connecting a resistance and an inductance at the secondary side port of the CT to get the equations for calculating the impedance. The iterative method is used to solve the equations, and the solution is revised to consider the nonlinearity of the core. The main variable in the equations is the variation of the secondary current with the resistance or inductance. To obtain the secondary current variation accurately, which is less than 1‱ of the current, a differential method is proposed, which is based on charging two capacitors and measuring the difference of their voltages instead of measuring each current separately first and then obtaining the current variation by subtraction. This is equivalent to saving two currents first and then measuring the current difference. The differential method avoids the problem of error amplification in the process of measuring two currents separately first and then subtracting them to obtain the current variation and solves the problem that two currents do not appear simultaneously. The results verify the correctness and accuracy of the proposed method and system. The acquisition of the excitation impedance is the basis for obtaining the working characteristics of CT cores, including magnetic and loss characteristics, as well as the error of CTs.

Effect of anaerobic digestion on odor and ammonia emission from land-applied cattle manure.

High ammonia (NH3) and odor emission can occur after land application of liquid animal manure. This study was aimed at evaluating NH3 loss and odor nuisance after field application of cattle manure and how it is affected by two anaerobic digestion strategies: i) digestion of cattle manure alone and ii) digestion with catch crops and dilution by water. A system of dynamic chambers with online measurements of NH3 and odorous compounds (summarized as odor activity value, OAV) was used. Two experiments were conducted under different temperature conditions. The results demonstrated that anaerobic digestion did not affect NH3 loss but did decrease OAV. Addition of catch crops and water to the digestion process reduced both NH3 loss and OAV. Cool temperature in one of the experiments had a large effect on both NH3 and odor emissions, and at high temperature the differences between treatments increased.

Exploring an online method of measuring implicit sequence-learning consciousness.

Existing methods for measuring implicit sequence-learning consciousness are conducted offline. Based on the traditional measurement of cued-generation task, this study implemented an online measurement method by converting a generation task into a forced-choice task to observe the dynamic changes of consciousness in the implicit sequence-learning process. In this study, we compared the performance of online measurement task and traditional sequence-learning tasks in 31 university students. The results revealed that the online indicators were significantly correlated with classic consciousness indicators and typical ERP components of consciousness. Without affecting the development of consciousness, the online measurement indicators were found to promptly and effectively reflect the gradually changing progression of consciousness in implicit sequence learning.

Automated ExEm-spFRET Microscope.

Excitation­emission-spectral unmixing-based fluorescence resonance energy transfer (ExEm-spFRET) microscopy exhibits excellent robustness in living cells. We here develop an automatic ExEm-spFRET microscope with 3.04 s of time resolution for a quantitative FRET imaging. The user-friendly interface software has been designed to operate in two modes: administrator and user. Automatic background recognition, subtraction, and cell segmentation were integrated into the software, which enables FRET calibration or measurement in a one-click operation manner. In administrator mode, both correction factors and spectral fingerprints are only calibrated periodically for a stable system. In user mode, quantitative ExEm-spFRET imaging is directly implemented for FRET samples. We implemented quantitative ExEm-spFRET imaging for living cells expressing different tandem constructs (C80Y, C40Y, C10Y, and C4Y, respectively) and obtained consistent results for at least 3 months, demonstrating the stability of our microscope. Next, we investigated Bcl-xL-Bad interaction by using ExEm-spFRET imaging and FRET two-hybrid assay and found that the Bcl-xL-Bad complexes exist mainly in Bad-Bcl-xL trimers in healthy cells and Bad-Bcl-xL2 trimers in apoptotic cells. We also performed time-lapse FRET imaging on our system for living cells expressing Yellow Cameleon 3.6 (YC3.6) to monitor ionomycin-induced rapid extracellular Ca2+ influx with a time interval of 5 s for total 250 s.

A Virtual Combustion Sensor Based on Ion Current for Lean-Burn Natural Gas Engine.

In this study, an innovative sensor was designed to detect the key combustion parameters of the marine natural gas engine. Based on the ion current, any engine structurally modified was avoided and the real-time monitoring for the combustion process was realized. For the general applicability of the proposed sensor, the ion current generated by a high-energy ignition system was acquired in a wide operating range of the engine. It was found that engine load, excess air coefficient (λ) and ignition timing all generated great influence on both the chemical and thermal phases, which indicated that the ion current was highly correlated with the combustion process in the cylinder. Furthermore, the correlations between the 5 ion current-related parameters and the 10 combustion-related parameters were analyzed in detail. The results showed that most correlation coefficients were relatively high. Based on the aforementioned high correlation, the novel sensor used an on-line algorithm at the basis of neural network models. The models took the characteristic values extracted from the ion current as the inputs and the key combustion parameters as the outputs to realize the online combustion sensing. Four neural network models were established according to the existence of the thermal phase peak of the ion current and two different network structures (BP and RBF). Finally, the predicted values of the four models were compared with the experimental values. The results showed that the BP (with thermal) model had the highest prediction accuracy of phase parameters and amplitude parameters of combustion. Meanwhile, RBF (with thermal) model had the highest prediction accuracy of emission parameters. The mean absolute percentage errors (MAPE) were mostly lower than 0.25, which proved a high accuracy of the proposed ion current-based virtual sensor for detecting the key combustion parameters.

Online measurement of dissolved carbon monoxide concentrations reveals critical operating conditions in gas fermentation experiments.

Syngas fermentation is one possible contributor to the reduction of greenhouse gas emissions. The conversion of industrial waste gas streams containing CO or H2 , which are usually combusted, directly reduces the emission of CO2 into the atmosphere. Additionally, other carbon-containing waste streams can be gasified, making them accessible for microbial conversion into platform chemicals. However, there is still a lack of detailed process understanding, as online monitoring of dissolved gas concentrations is currently not possible. Several studies have demonstrated growth inhibition of Clostridium ljungdahlii at high CO concentrations in the headspace. However, growth is not inhibited by the CO concentration in the headspace, but by the dissolved carbon monoxide tension (DCOT). The DCOT depends on the CO concentration in the headspace, CO transfer rate, and biomass concentration. Hence, the measurement of the DCOT is a superior method to investigate the toxic effects of CO on microbial fermentation. Since CO is a component of syngas, a detailed understanding is crucial. In this study, a newly developed measurement setup is presented that allows sterile online measurement of the DCOT. In an abiotic experiment, the functionality of the measurement principle was demonstrated for various CO concentrations in the gas supply (0%-40%) and various agitation rates (300-1100 min-1 ). In continuous stirred tank reactor fermentation experiments, the measurement showed reliable results. The production of ethanol and 2,3-butanediol increased with increasing DCOT. Moreover, a critical DCOT was identified, leading to the inhibition of the culture. Thus, the reported online measurement method is beneficial for process understanding. In future processes, it can be used for closed-loop fermentation control.

Continuous measurement of reactive oxygen species inside and outside of a residential house during summer.

Reactive oxygen species (ROS) are an important contributor to adverse health effects associated with ambient air pollution. Despite infiltration of ROS from outdoors, and possible indoor sources (eg, combustion), there are limited data available on indoor ROS. In this study, part of the second phase of Air Composition and Reactivity from Outdoor aNd Indoor Mixing campaign (ACRONIM-2), we constructed and deployed an online, continuous, system to measure extracellular gas- and particle-phase ROS during summer in an unoccupied residence in St. Louis, MO, USA. Over a period of one week, we observed that the non-denuded outdoor ROS (representing particle-phase ROS and some gas-phase ROS) concentration ranged from 1 to 4 nmol/m3 (as H2 O2 ). Outdoor concentrations were highest in the afternoon, coincident with peak photochemistry periods. The indoor concentrations of particle-phase ROS were nearly equal to outdoor concentrations, regardless of window-opening status or air exchange rates. The indoor/outdoor ratio of non-denuded ROS (I/OROS ) was significantly less than 1 with windows open and even lower with windows closed. Combined, these observations suggest that gas-phase ROS are efficiently removed by interior building surfaces and that there may be an indoor source of particle-phase ROS.

Developing an Online Measurement Device Based on Resistance Sensor for Measurement of Single Grain Moisture Content in Drying Process.

The online measurement of moisture content for grains is an essential technology to realize real-time tracking and control, improve drying quality and reduce energy consumption of the drying process. To improve the measurement accuracy and reliability of the dynamic measurement process as well as expand the application scope of the device, the present work constructed an experimental equipment for determining dynamic resistance characteristics of a single grain. The relations between moisture content and real-time resistance waveform were revealed, and an analytical calculation method of peak value and peak area of waveform was proposed, which correctly revealed the electrical measurement properties of grain. The results demonstrated that the gap width between the electrodes had large influence on the sensor's performance. Moreover, an online measuring device was developed based on the experimental analysis and calculation method, and the test results in both lab and field for different grains showed that online real-time absolute measurement error are within ±0.5% in the varied moisture content (10-35%w.b.) and the temperature (-20-50 °C). The main results and the developed device might provide technical support for developing intelligent grain drying equipment.

Characteristics of severe life events, attachment style, and depression - Using a new online approach.

OBJECTIVES: Severe life events are established as provoking agents for depression in combination with vulnerability factors. Identifying features of severe events improves the prediction of disorder but are rarely utilized, mainly because life event research is increasingly dominated by self-report checklists with no capacity for inferring such characteristics. This paper investigates the association of severe life events' features with depression and insecure attachment styles using a new online measure of life events in a clinical and control sample. METHODS: A total of 202 participants (75 clinical and 127 matched control participants), taken from an earlier national Depression Case Control genetic study and followed up after 12 years, completed the Computerised Life Events Assessment Record to assess characteristics of life events, the Vulnerable Attachment Style Questionnaire to measure attachment insecurity, and the General Health Questionnaire to measure depression. RESULTS: The clinical group had higher self-reported depression, severe life events, and insecure attachment style. They also reported more loss, danger, humiliation, and trauma severe events. Intra-respondent analysis showed individuals experiencing these types of events were more likely to report depression. Insecure attachment style and severe life events were both significantly related to recent depression and history of depressive disorder. Anxious attachment style was significantly related to relationship events and bereavements, as well as severe loss or humiliation events, whereas avoidant style was not. CONCLUSIONS: Identifying salient features of severe life events improves associations with depression and insecure attachment style. Utilizing a new online approach can aid research and clinical approaches for depression at low cost. PRACTITIONER POINTS: Salient features of severe life events (e.g., loss, humiliation) give insight into the potential impact on attachment vulnerability and depression. Clinicians and researchers can use online methods to economically gain detailed life event information needed for clinical formulation and valid data on stressors. The self-reported scale for recent depression is only a proxy measure of clinical disorder, but the clinical group selection is a more robust criterion for depression history.

Highly functionalized organic nitrates in the southeast United States: Contribution to secondary organic aerosol and reactive nitrogen budgets.

Speciated particle-phase organic nitrates (pONs) were quantified using online chemical ionization MS during June and July of 2013 in rural Alabama as part of the Southern Oxidant and Aerosol Study. A large fraction of pONs is highly functionalized, possessing between six and eight oxygen atoms within each carbon number group, and is not the common first generation alkyl nitrates previously reported. Using calibrations for isoprene hydroxynitrates and the measured molecular compositions, we estimate that pONs account for 3% and 8% of total submicrometer organic aerosol mass, on average, during the day and night, respectively. Each of the isoprene- and monoterpenes-derived groups exhibited a strong diel trend consistent with the emission patterns of likely biogenic hydrocarbon precursors. An observationally constrained diel box model can replicate the observed pON assuming that pONs (i) are produced in the gas phase and rapidly establish gas-particle equilibrium and (ii) have a short particle-phase lifetime (∼2-4 h). Such dynamic behavior has significant implications for the production and phase partitioning of pONs, organic aerosol mass, and reactive nitrogen speciation in a forested environment.

Modeling and Experimental Study for Online Measurement of Hydraulic Cylinder Micro Leakage Based on Convolutional Neural Network.

Internal leakage is the most common failure of hydraulic cylinder; when it increases, it decreases volumetric efficiency, pressure and speed of the hydraulic cylinder, and can seriously affect the normal operation of the hydraulic cylinder, so it is important to measure it, especially to measure it online. Firstly, the principle of internal leakage online measurement is proposed, including the online measurement system, the fixed mode of the strain gauge and the mathematical model of the flow-strain signal conversion. Secondly, an experimental system is established to collect internal leakages and strain values, and the data is processed. Finally, the convolutional neural network (CNN), BP neural network (BPNN), Radial Basis Function Network (RBF), and Support Vector Regression (SVR) are used to predict the hydraulic cylinder leakage; the comparison of experimental results show that the CNN has high accuracy and high efficiency. This study provides a new idea for online measurement of small flow on other hydraulic components.

Multispectral Fluorescence Imaging Technique for On-Line Inspection of Fecal Residues on Poultry Carcasses.

Rapid and reliable inspection of food is essential to ensure food safety, particularly in mass production and processing environments. Many studies have focused on spectral imaging for poultry inspection; however, no research has explored the use of multispectral fluorescence imaging (MFI) for on-line poultry inspection. In this study, the feasibility of MFI for on-line detection of fecal matter from the ceca, colon, duodenum, and small intestine of poultry carcasses was investigated for the first time. A multispectral line-scan fluorescence imaging system was integrated with a commercial poultry conveying system, and the images of chicken carcasses with fecal contaminants were scanned at processing line speeds of one, three, and five birds per second. To develop an optimal detection and classification algorithm to distinguish upper and lower feces-contaminated parts from skin, the principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) were first performed using the spectral data of the selected regions, and then applied in spatial domain to visualize the feces-contaminated area based on binary images. Our results demonstrated that for the spectral data analysis, both the PCA and PLS-DA can distinguish the high and low feces-contaminated area from normal skin; however, the PCA analysis based on selected band ratio images (F630 nm/F600 nm) exhibited better visualization and discrimination of feces-contaminated area, compared with the PLS-DA-based developed chemical images. A color image analysis using histogram equalization, sharpening, median filter, and threshold value (1) demonstrated 78% accuracy. Thus, the MFI system can be developed utilizing the two band ratios for on-line implementation for the effective detection of fecal contamination on chicken carcasses.

Novel technique for high throughput measurement of active monooxygenase concentration.

Absorbance measurements via transmitting light spectroscopy in microtiter plates are established for high throughput screening of biological systems. These measurements allow for the determination of important process parameters within a short time. However, absorbance determination via transmitted light measurements is not always feasible. As for carbon monoxide difference absorbance spectroscopy, used for concentration measurements of active P450 monooxygenases (P450s), security standards, and consistent gassing have to be addressed. In this study, a non-invasive online measuring principle for absorbance via scattered light is proposed. Based on optical fiber measurements, a decrease in scattered light signals at 450 nm wavelength of reflecting polymer particles is observed, and P450 concentrations are calculated. In this way, high throughput determination of P450 concentrations in a secure, gas-tight environment is realized. The designed method was successfully applied to concentration measurements and carbon monoxide (CO) saturation kinetics ranging from 0.3 to 5.0 µM P450 BM3 achieving a measurement accuracy of ±0.05 µM P450. Biotechnol. Bioeng. 2017;114: 929-933. © 2016 Wiley Periodicals, Inc.

Online Measurement of Melt-Pool Width in Direct Laser Deposition Process Based on Binocular Vision and Perspective Transformation.

Direct laser deposition (DLD) requires high-energy input and causes poor stability and portability. To improve the deposited layer quality, conducting online measurements and feedback control of the dimensions, temperature, and other melt-pool parameters during deposition is essential. Currently, melt-pool dimension measurement is mainly based on machine vision methods, which can mostly detect only the deposition direction of a single melt pool, limiting their measurement range and applicability. We propose a binocular-vision-based online measurement method to detect the melt-pool width during DLD. The method uses a perspective transformation algorithm to align multicamera measurements into a single-coordinate system and a fuzzy entropy threshold segmentation algorithm to extract the melt-pool true contour. This effectively captures melt-pool width information in various deposition directions. A DLD measurement system was constructed, establishing an online model that maps the melt-pool width to the offline deposited layer width, validating the accuracy of the binocular vision system in measuring melt-pool width at different deposition angles. The method achieved high accuracy for melt-pool measurements within certain deposition angle ranges. Within the 30°-60° measurement range, the average error is 0.056 mm, with <3% error. The proposed method enhances the detectable range of melt-pool widths, improving cladding layers and parts.

Quantification of N and C cycling during aerobic composting, including automated direct measurement of N2, N2O, NO, NH3, CO2 and CH4 emissions.

Closing the carbon (C) and nitrogen (N) balance has yet to be achieved in aerobic bioprocess due to current methodological drawbacks in the frequency of sampling and detection and the challenge in direct measurement of instantaneous N2 emission. To address this issue, a novel system was developed enabling simultaneous and online determination of gaseous C and N species (N2, N2O, NO, NH3, CO2 and CH4) from aerobic composting at a high frequency of 120 times·d-1. A helium­oxygen gas mixture was used to replace the air in the system to enable direct measurement of N2 emission, and three different gas exchange methods were assessed in their ability to minimize atmospheric background N2: 1) the N2-free gas purging method; 2) one cycle of the evacuation-refilling procedure; 3) one cycle of evacuating and refilling followed by N2-free gas purging. Method 3 was demonstrated as an optimum N2-removal method, and background N2 concentrations decreased to ~66 µmol·mol-1 within 11.6 h. During the N2-free gas purging period, low temperature incubation at 15 °C reduced CO2, CH4, NO, N2O and NH3 losses by 80.5 %, 41-fold, 10-fold, 11,403-fold and 61.4 %, respectively, compared with incubation at 30 °C. Therefore, a fast and low-perturbation N2 removal method was developed, namely the evacuating/refilling-low temperature purging method. Notably, all C and N gases exhibited large within-day variations during the peak emission period, which can be addressed by high-frequency measurement. Based on the developed method, up to 97.8 % of gaseous C and 95.6 % of gaseous N losses were quantified over a 43-day compost incubation, with N2 emission accounting (on average) for 5.8 % of the initial total N. This system for high frequency measurement of multiple gases (including N2) provides a novel tool for obtaining a deeper understanding of C and N turnover and more accurate estimation of reactive N and greenhouse gas emissions during composting.

[On-line Measurement of Trace Elements in PM2.5 in Winter in Urban Taiyuan, China: Levels and Source Apportionment].

In order to better identify the sources of PM2.5 in Taiyuan, hourly concentrations of 13 trace elements (K, Ca, Ba, Cr, Mn, Fe, Cu, Ni, Zn, As, Se, Pb, and Sr) in PM2.5 were monitored at an urban site in Taiyuan from January 1 to 29, 2022. The pollution characteristics of trace elements were analyzed and sources were apportioned using positive matrix factorization (PMF). The results showed that the average concentration of 13 total trace elements was (3901.6±2611.2) ng·m-3, which accounted for (7.1±7.7)% of PM2.5. The three dominant elements were Fe[(1319.5±1003.5 ng·m-3)], Ca[(1181.0±1241.6 ng·m-3)], and K[(883.3±357.3 ng·m-3)]. The average concentrations of Cr(Ⅵ) (4.6 ng·m-3) and As (11.2 ng·m-3) exceeded the guideline values of the Chinese National Ambient Air Quality Standard (GB 3095-2012) and the World Health Organization. Fugitive dust, vehicle emissions, industry, stainless-steel production, biomass burning and waste incineration, residential coal combustion, and industrial coal combustion were identified by the PMF model, which accounted for 45.5%, 1.4%, 15.8%, 23.7%, 5.5%, and 8.1%, respectively, of the total elements.Compared with those during the stages of pollution development and dissipation, the contributions of industrial coal combustion, residential coal combustion, and biomass burning and waste incineration to the total elements during the pollution maintenance stage of the PM2.5 pollution episode increased significantly, contributing 11.8%, 7.1%, and 28.1%, respectively, of the total elements. These results could provide scientific references for the refined source apportionment of PM2.5 in other areas.

Concurrent measurements of nitrate at urban and suburban sites identify local nitrate formation as a driver for urban episodic PM2.5 pollution.

Nitrate (NO3-) is often among the leading components of urban particulate matter (PM) during PM pollution episodes. However, the factors controlling its prevalence remain inadequately understood. In this work, we analyzed concurrent hourly monitoring data of NO3- in PM2.5 at a pair of urban and suburban locations (28 km apart) in Hong Kong for a period of two months. The concentration gradient in PM2.5 NO3- was 3.0 ± 2.9 (urban) vs. 1.3 ± 0.9 µg m-3 (suburban) while that for its precursors nitrogen oxides (NOx) was 38.1 vs 4.1 ppb. NO3- accounted for 45 % of the difference in PM2.5 between the sites. Both sites were characterized to have more available NH3 than HNO3. Urban nitrate episodes, defined as periods of urban-suburban NO3- difference exceeding 2 µg m-3, constituted 21 % of the total measurement hours, with an hourly NO3- average gradient of 4.2 and a peak value of 23.6 µg m-3. Our comparative analysis, together with 3-D air quality model simulations, indicates that the high NOx levels largely explain the excessive NO3- concentrations in our urban site, with the gas phase HNO3 formation reaction contributing significantly during the daytime and the N2O5 hydrolysis pathway playing a prominent role during nighttime. This study presents a first quantitative analysis that unambiguously shows local formation of NO3- in urban environments as a driver for urban episodic PM2.5 pollution, suggesting effective benefits of lowering urban NOx.

Impact of different trace elements on metabolic routes during heterotrophic growth of C. ljungdahlii investigated through online measurement of the carbon dioxide transfer rate.

Synthesis gas fermentation using acetogenic clostridia is a rapidly increasing research area. It offers the possibility to produce platform chemicals from sustainable C1 carbon sources. The Wood-Ljungdahl pathway (WLP), which allows acetogens to grow autotrophically, is also active during heterotrophic growth. It acts as an electron sink and allows for the utilization of a wide variety of soluble substrates and increases ATP yields during heterotrophic growth. While glycolysis leads to CO2 evolution, WLP activity results in CO2 fixation. Thus, a reduction of net CO2 emissions during growth with sugars is an indicator of WLP activity. To study the effect of trace elements and ventilation rates on the interaction between glycolysis and the WLP, the model acetogen Clostridium ljungdahlii was cultivated in YTF medium, a complex medium generally employed for heterotrophic growth, with fructose as growth substrate. The recently reported anaRAMOS device was used for online measurement of metabolic activity, in form of CO2 evolution. The addition of multiple trace elements (iron, cobalt, manganese, zinc, nickel, copper, selenium, and tungsten) was tested, to study the interaction between glycolysis and the Wood ljungdahl pathway. While the addition of iron(II) increased growth rates and ethanol production, added nickel(II) increased WLP activity and acetate formation, reducing net CO2 production by 28%. Also, higher CO2 availability through reduced volumetric gas flow resulted in 25% reduction of CO2 evolution. These online metabolic data demonstrate that the anaRAMOS is a valuable tool in the investigation of metabolic responses i.e. to determine nutrient requirements that results in reduced CO2 production. Thereby the media composition can be optimized depending on the specific goal.

Near-infrared hyperspectral imaging for online measurement of the viability detection of naturally aged watermelon seeds.

The viability status of seeds before sowing is important to farmers as it allows them to make yield predictions. Monitoring the seed quality in a rapid and nondestructive manner may create a perfect solution, especially for industrial sorting applications. However, current offline laboratory-based strategies employed for the monitoring of seed viability are time-consuming and thus cannot satisfy industrial needs where there is a substantial number of seeds to be analyzed. In this study, we describe a prototype online near-infrared (NIR) hyperspectral imaging system that can be used for the rapid detection of seed viability. A wavelength range of 900-1700 nm was employed to obtain spectral images of three different varieties of naturally aged watermelon seed samples. The partial least square discriminant analysis (PLS-DA) model was employed for real-time viability prediction for seed samples moving through a conveyor unit at a speed of 49 mm/sec. A suction unit was further incorporated to develop the online system and it was programmatically controlled to separate the detected viable seeds from nonviable ones. For an external validation sample set showed classification accuracy levels of 91.8%, 80.7%, and 77.8% in relation to viability for the three varieties of watermelon seed with healthy seedling growth. The regression coefficients of the classification model distinguished some chemical differences in viable and nonviable seed which was verified by the chromatographic analysis after the detection of the proposed online system. The results demonstrated that the developed online system with the viability prediction model has the potential to be used in the seed industry for the quality monitoring of seeds.