Abstract
Moisture content is a critical variable for the harvesting, processing, storing and marketing of cereal grains, oilseeds and legumes. Efficient and accurate determination of grain moisture content even with advanced nondestructive techniques, remains a challenge due to complex water-retaining biological structures and hierarchical composition and geometry of grains that affect measurement interpretation and require specific grain-dependent calibration. We review (1) the primary factors affecting permittivity measurements used in practice for inferring moisture content in grains; (2) develop novel methods for estimating critical parameters for permittivity modeling including packing density, porosity, water binding surface area and water phase permittivity and (3) represent the permittivity of packs of grains using dielectric mixture theory as a function of moisture content applied to high moisture corn (as a model grain). Grain permittivity measurements are affected by their free and bound water contents, chemical composition, temperature, constituent shape, phase configuration and measurement frequency. A large fraction of grain water is bound exhibiting reduced permittivity compared to that of free water. The reduced mixture permittivity and attributed to hydrophilic surfaces in starches, proteins and other high surface area grain constituents. The hierarchal grain structure (i.e., kernel, starch grain, lamella, molecule) and the different constituents influence permittivity measurements due to their layering, geometry (i.e., kernel or starch grain), configuration and water-binding surface area. Dielectric mixture theory offers a physically-based approach for modeling permittivity of agricultural grains and similar granular media.
Highlights
Determination of the moisture content of cereal grains, oilseeds and legumes is crucial in three respects
In the following we focus on high moisture corn, where determination of its water content has historically been error-prone relative to grain harvested at lower moisture contents [12–14]
For dielectric mixture theory and most electromagnetic-based sensing are interested in volumetric constituent quantities and require 4tohf e39 volum content, Mv, which we obta athcoemdbirnyatioorn wof ebot-ubnadsainsdmfreoeiwstauterrerecsounltsteinnmt ourseicnogmptlhexewgartaerincobntuenlkt-pderemnisttiitvyit,yρb, and rferlaeteiowns.aStienrc,eρwwa,tearscofnotlelnotwdestermination is the goal of our permittivity measurements, much of this review is devoted to defining or estimating the bound-free water relations
Summary
Determination of the moisture content of cereal grains, oilseeds and legumes is crucial in three respects. (1) From a technological standpoint, harvesting, drying, storing and milling operations are all based on grain moisture levels. (2) Analytically, all methods for moisture content determination are related to dry matter or a standard moisture content. (3) In commercial applications, the pricing of grain is a function of moisture content throughout the entire marketing process. The vast quantity of grain and oilseeds marketed worldwide accentuates the critical need for the advancement of the science and technologies aimed at improving the accuracy of moisture content determination in cereal grains and biological materials in general This is especially true in developing countries where grain moisture determination often requires low-tech or alternative methods [18]. Much of the reported measurement accuracy of grain moisture meters has been carried out under controlled conditions in scientific laboratories, a question remains as to the measurement capability under ‘real world’ conditions where grain variety may deviate from calibration standards or where conditions are not well controlled Since both temperature and packing density are routinely determined by moisture meters, other factors affecting permittivity of cereal grains such as constituent composition and form of water (i.e., bound or free) remains a topic of ongoing research [8,23–26]. In the following we discuss these factors followed by a sampling of dielectric mixture models
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
