Provided is a method for monitoring a manufacturing process of an agricultural product. The method utilizes hyperspectral imaging and comprises scanning at least one region along a sample of agricultural product using at least one light source of a single or different wavelengths; generating hyperspectral images from the at least one region; determining a spectral fingerprint for the sample of agricultural product from the hyperspectral images; and comparing the spectral fingerprint so obtained to a spectral fingerprint database containing a plurality of fingerprints obtained at various points of the manufacturing process, using a computer processor, to determine which point in the manufacturing process the sample has progressed to.

A method for removing foreign matter from an agricultural product stream of a manufacturing process. The method includes conveying a product stream past an inspection station; scanning a region of the agricultural product stream as it passes the inspection station using at least one light source of a single or different wavelengths; generating hyperspectral images from the scanned region; determining a spectral fingerprint for the agricultural product stream from the hyperspectral images; comparing the spectral fingerprint obtained in step (c) to a spectral fingerprint database containing a plurality of fingerprints using a computer processor to determine whether foreign matter is present and, if present, generating a signal in response thereto; and removing a portion of the conveyed product stream in response to the signal. A system for detecting foreign matter within an agricultural product stream is also provided.

A method for removing foreign matter from an agricultural product stream of a manufacturing process. The method includes conveying a product stream past an inspection station; scanning a region of the agricultural product stream as it passes the inspection station using at least one light source of a single or different wavelengths; generating hyperspectral images from the scanned region; determining a spectral fingerprint for the agricultural product stream from the hyperspectral images; comparing the spectral fingerprint obtained in step (c) to a spectral fingerprint database containing a plurality of fingerprints using a computer processor to determine whether foreign matter is present and, if present, generating a signal in response thereto; and removing a portion of the conveyed product stream in response to the signal. A system for detecting foreign matter within an agricultural product stream is also provided.

Provided is a method for blending of agricultural product utilizing hyperspectral imaging. At least one region along a sample of agricultural product is scanned using at least one light source of different wavelengths. Hyperspectral images are generated from the at least one region. A spectral fingerprint for the sample of agricultural product is formed from the hyperspectral images. A plurality of samples of agricultural product is blended based on the spectral fingerprints of the samples according to parameters determined by executing a blending algorithm.

Provided is a method for blending of agricultural product utilizing hyperspectral imaging. At least one region along a sample of agricultural product is scanned using at least one light source of different wavelengths. Hyperspectral images are generated from the at least one region. A spectral fingerprint for the sample of agricultural product is formed from the hyperspectral images. A plurality of samples of agricultural product is blended based on the spectral fingerprints of the samples according to parameters determined by executing a blending algorithm.

A method for removing foreign matter from an agricultural product stream of a manufacturing process. The method includes conveying a product stream past an inspection station; scanning a region of the agricultural product stream as it passes the inspection station using at least one light source of a single or different wavelengths; generating hyperspectral images from the scanned region; determining a spectral fingerprint for the agricultural product stream from the hyperspectral images; comparing the spectral fingerprint obtained in step (c) to a spectral fingerprint database containing a plurality of fingerprints using a computer processor to determine whether foreign matter is present and, if present, generating a signal in response thereto; and removing a portion of the conveyed product stream in response to the signal. A system for detecting foreign matter within an agricultural product stream is also provided.

A method for removing foreign matter from an agricultural product stream of a manufacturing process. The method includes conveying a product stream past an inspection station; scanning a region of the agricultural product stream as it passes the inspection station using at least one light source of a single or different wavelengths; generating hyperspectral images from the scanned region; determining a spectral fingerprint for the agricultural product stream from the hyperspectral images; comparing the spectral fingerprint obtained in step (c) to a spectral fingerprint database containing a plurality of fingerprints using a computer processor to determine whether foreign matter is present and, if present, generating a signal in response thereto; and removing a portion of the conveyed product stream in response to the signal. A system for detecting foreign matter within an agricultural product stream is also provided.

Provided is a method for blending of agricultural product utilizing hyperspectral imaging. At least one region along a sample of agricultural product is scanned using at least one light source of different wavelengths. Hyperspectral images are generated from the at least one region. A spectral fingerprint for the sample of agricultural product is formed from the hyperspectral images. A plurality of samples of agricultural product is blended based on the spectral fingerprints of the samples according to parameters determined by executing a blending algorithm.

Provided is a method for blending of agricultural product utilizing hyperspectral imaging. At least one region along a sample of agricultural product is scanned using at least one light source of different wavelengths. Hyperspectral images are generated from the at least one region. A spectral fingerprint for the sample of agricultural product is formed from the hyperspectral images. A plurality of samples of agricultural product is blended based on the spectral fingerprints of the samples according to parameters determined by executing a blending algorithm.

The disclosed technology pertains to a customizable smokable whole leaf wrap and its multi-step manufacturing process that includes size screening, curing, pasteurization, adhesive application, sheet formation, cutting, and drying. The process is adaptable, offering various alternative methods and embodiments, enabling a wide array of wrap properties, flavors, and functionalities. This flexibility extends to the use of different strains, plant materials, infusions, adhesives, treatments, and manufacturing techniques. Certain embodiments can incorporate flavor-enhancing compounds, essential oils, herbal extracts, heat-resistant coatings, odor-absorbing treatments, built-in filters, or ventilation systems for an optimized smoking experience. The technology also emphasizes environmental sustainability with possibilities such as biodegradable adhesives, closed-loop manufacturing, and natural insect repellents, delivering a safe, quality, and environmentally responsible product tailored to consumer needs and preferences.