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ARS Home » Southeast Area » Stoneville, Mississippi » Cotton Ginning Research » Research » Research Project #447089

Research Project: Characterization of Hemp Hurd for Industry Utilization

Location: Cotton Ginning Research

Project Number: 6066-41440-009-023-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 27, 2024
End Date: Sep 30, 2025

Objective:
The overall goal of this work is to create the baseline information that can lead to classification, valuation, and utilization of the hemp hurd as a feedstock and emerging product with an emphasis on methods that can lead to performance and classification standards. The specific objectives are: 1. To chemically characterize the constituent components of hurd, 2. To physically characterize hurd material as a function of the processing methods, 3. To identify the densification and transportation durability characteristics of hurd, and 4. To determine the storage and storability properties of hurd in order to maintain quality prior to utilization.

Approach:
Objective 1 will focus on the classification of hurd structural carbohydrates at multiple points in the value chain. Lignin, cellulose, and hemicellulose present in hurd directly inform the value and function of the materials for industrial and agricultural applications. This approach will employ detergent analysis typically seen in forage analysis along with dry combustion to identify total carbon, nitrogen, and mineral components. Further analysis will focus on NIR reflectance methods to scale and create inline testing for chemical properties. Ideally samples for this analysis would originate from multiple growing seasons and growing locations to determine the stability of the constituent materials under various growing conditions and will be replicated to ensure statistical suitability of the analysis. Objective 2 recognizes that hurd can enter the value stream from many different points after having been handled and processed with a multitude of methods. This objective will focus on documenting the particle size, volume, bulk density, and presence of extraneous matter in the resulting materials. Methods for this objective will utilize pynchometer-based volumetric estimation, traditional bulk density estimation with control volumes, and machine vision estimation of particle size and frequency. Material separation such as sieving, air columns, and machine vision will identify non-hurd materials present. Understand the logistics of handling hurd will be essential for the establishment of a domestic industrial hemp industry, Objective 3 address these challenges. For hurd to find effective utilization in secondary markets, transportation logistics and methods must be considered. The materials may transport effectively as loose fill but often bulk density as loose fill makes transportation over meaningful distance infeasible. Densification and the creation of identifiable modular units opens more opportunities to open additional markets to hurd. This methods will employ physical compression as an approach for transportation preparation. Once densified, the material suitability for further processing must be analyzed as described previously. The durability of the densified unit along with proper strapping or baling cover for integrity during transport will be assessed. Objective 4 recognizes that utilization requires understanding how material properties are maintained or change under various storage regimes. Moisture content and time in storage will all have a direct impact on the hurd and its associated physical and chemical properties. Hurd will be stored in a static environmental chamber to determine the impacts of temperature and relative humidity on equilibrium moisture content. These resulting characteristic curves inform drying strategies and the energy required to remove a unit of moisture from a unit of stored material. Degradation under storage will be assessed by measuring changes in structural carbohydrate content and the presence of microbiological degradation under storage times and moisture contents. This data should inform an understanding of quality degradation and functional loss under suboptimal storage.