A method for identifying converters from tobacco seedling population. The method includes: 1) sowing and cultivating tobacco seeds to be identified for 45-55 days; sampling a plurality of leaf disks from each of 45-55 days old seedlings; 2) incubating the plurality of leaf disks of each seedling in a sealed container at 37° C. for 10-12 hours, thereby obtaining a plurality of incubated tobacco leaves of each seedling; 3) immersing the plurality of incubated tobacco leaves of each seedling in an extractant, extracting alkaloids and obtaining an extract of each seedling; 4) analyzing the amounts of nicotine and nornicotine in the alkaloids extract of each seedling; and 5) automatically recognizing peaks of the alkaloids extract of each seedling, and calculating the percent nicotine conversion (PNC) and the pseudo percent nicotine conversion (PPNC).

The present invention relates to method and an apparatus for quantitatively analyzing a gaseous process stream, in particular a stream from a process for producing ethylene carbonate and/or ethylene glycol, in particular where such stream comprises gaseous organic iodides.

The present invention generally pertains to methods of identifying and characterizing host cell proteins. In particular, the present invention pertains to the use of size exclusion chromatography in non-denaturing or denaturing conditions to enrich a sample for host cell proteins and characterize the binding of host cell proteins to a protein of interest.

The present invention relates to methods for determining the change in concentration of a substance in solution over time by continuously monitoring in real time. In particular, the present invention relates to methods for continuously monitoring the concentration of compounds during the manufacturing process of biomolecules.

The present invention relates to method and an apparatus for quantitatively analyzing a gaseous process stream, in particular a stream from a process for producing ethylene carbonate and/or ethylene glycol, in particular where such stream comprises gaseous organic iodides.

The present invention relates to methods for determining the change in concentration of a substance in solution over time by continuously monitoring in real time. In particular, the present invention relates to methods for continuously monitoring the concentration of compounds during the manufacturing process of biomolecules.

The present invention relates to method and an apparatus for quantitatively analyzing a gaseous process stream, in particular a stream from a process for producing ethylene carbonate and/or ethylene glycol, in particular where such stream comprises gaseous organic iodides.

The disclosure features methods that include obtaining a vibrational spectrum of a solution in a biological manufacturing system, analyzing the vibrational spectrum using a first chemometrics model to determine a value of a first quality attribute associated with the solution, analyzing the vibrational spectrum using a second chemometrics model to determine a value of a second quality attribute associated with the solution, and adjusting at least one parameter of a purification unit of the biological manufacturing system based on at least one of the values of the first and second quality attributes.

A device for testing performance of photocatalytic ozonation in degradation of volatile organic compounds. The device includes an air generator, an oxygen cylinder, a volatile organic compound cylinder, a mass flow meter, an ozone generator, a humidifier, a thermohygrometer, a gas mixer, a light source, a plate-type reactor, an ozone analyzer, a gas chromatographic instrument, a first valve, a second valve, a third valve and a tail gas treatment unit; The experimental device of the present invention is suitable for the experiment of photocatalytic degradation of volatile organic gases in mixed gas, and has the advantages of wide experimental conditions, simple structure, convenient use, reliable performance, etc.

The present application discloses method and sewer (111) for detecting faults associated with a gas chromatograph device (100) in a process plant. The gas chromatograph device (100) is associated with a database (110) configured to store a measured chromatogram, and historic chromatograms. Initially, the server receives the measured chromatogram from the database. Upon receiving the measured chromatogram, the server is configured to detect at least one real-time symptom for measured chromatogram. The real-time symptoms may be detected by comparing the historic chromatograms with predetermined configuration data to the measured chromatogram. Upon detecting the real-time symptoms, the server is configured to determine faults associated with the gas chromatograph device. The faults are determined by mapping the real-time symptoms and fault signature data received from the database. The fault signature data is generated using machine learning model trained by providing the faults and the historic gas chromatogram.