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.

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 and apparatus are provided for processing whole tobacco plants. The method includes cutting the whole tobacco plants into segments in a segmenter assembly, classifying the segments by leaf characteristics, separating leaf material from a waste material stream of undesirable stalk and shatter material for each class of leaf characteristics and reclaiming portions of leaf material trapped in the waste material and recycling the reclaimed portions of leaf material to the segmenter assembly. The apparatus includes a stalk segmenter assembly, a processor assembly, a plurality of cleaning conveyor modules and a cyclonic separator system to reclaim small bits of leaf from the waste stream and return them through a rotary airlock to the segmenter assembly for reprocessing.

A method and apparatus are provided for processing whole tobacco plants. The method includes cutting the whole tobacco plants into segments in a segmenter assembly, classifying the segments by leaf characteristics, separating leaf material from a waste material stream of undesirable stalk and shatter material for each class of leaf characteristics and reclaiming portions of leaf material trapped in the waste material and recycling the reclaimed portions of leaf material to the segmenter assembly. The apparatus includes a stalk segmenter assembly, a processor assembly, a plurality of cleaning conveyor modules and a cyclonic separator system to reclaim small bits of leaf from the waste stream and return them through a rotary airlock to the segmenter assembly for reprocessing.

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 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.