Kernel Moisture Research Articles

A regional analysis model of maize kernel moisture

AbstractWith the popularization of late‐maturing and high‐yielding maize (Zea mays L.) hybrids, high kernel moisture concentration at the usual harvest time has resulted in increased kernel breakage and additional drying costs. To achieve low kernel moisture at harvest in China's maize‐growing areas, there is a need for the selection of fast dry‐down hybrids and the prediction of the ideal harvest time. During 2014–2017, the time‐series kernel moisture concentrations of three maize hybrids were measured in the field in three major maize‐producing regions in China. Our goal was to accurately predict maize kernel dry‐down in the field. We found that the Logistic Power model M = 90/[1 + (T/a)b] could be used to accurately predict the entire dry‐down process of maize kernels across hybrids and regions (concordance correlation coefficient, 0.884–0.996; RMSE, 2.76–5.16%; R2, .943–.986; and coefficient of residual mass, −0.09–0.14), where M is the kernel moisture concentration (wet basis), a and b are parameters that reflect the dry‐down characteristics of the hybrids, and T is the thermal time (°C d) from silking based on mean daily temperature over the periods of grain‐filling and grain‐drying. This work provides a new and convenient model for predicting kernel moisture concentration and evaluating the dry‐down characteristics of hybrids using parameters a and b.

Nondestructive measurement of husk-covered corn kernel layer dynamic moisture content in the field

Corn kernel moisture content is the most frequently used indicator for kernel maturity prediction and determination of the appropriate mechanized harvesting time. Corn varieties with lower moisture contents and thus faster dehydration of the corn kernels after physiological maturity are suitable for high plant density and mechanized harvesting. However, nondestructive measurement of the dynamic moisture content of the husk-covered corn kernel layer before physiological maturity in the field remains challenging at present. Therefore, in this study, a nondestructive measurement method based on the vector reflection coefficient measurement technique is proposed and developed for in situ monitoring of the husk-covered corn kernel layer moisture in the field. Based on the one-port calibration procedure used for the handheld moisture detection device, quadratic regression models were established for the corn kernel layer moisture using impedance parameters from 51 husk-covered corn samples. Results showed that this method enabled nondestructive estimation of the husk-covered corn kernel layer moisture (R2=0.62) with a 3.53% root mean square error (RMSE) using a serial capacitor Cs and the husk moisture (R2=0.85) with a RMSE of 7.12%. Additionally, intact corn ears were measured in the field from the dent stage to the maturity stage using this device to investigate the dynamic moisture contents of the kernels and husks. Results showed that the measured moisture content of kernels before physiological maturity followed exponential decay functions with increasing numbers of days, and the mean difference between the measured kernel moisture contents of the intact corn ears and the oven-drying moisture contents of these kernels is 3.72%. In conclusion, the handheld moisture detection device allows us to measure the moisture of husk-covered corn kernel layers nondestructively before maturity in the field. This study thus provides a new way to obtain corn kernel dehydration curves in situ before maturity and estimate the corn maturity time.

Girdling Effects on Fruit Maturity, Kernel Quality, and Nutritional Value of Walnuts (Juglans regia L.) alongside the Effects on Leaf Physiological Characteristics

Girdling, based on the accumulation of photosynthetic products above the girdling zone, is a common technique applied to tree species to increase the yield and fruit quality. The aim of this study was to investigate the girdling effects on photosynthesis and soluble sugars (Sols) of leaves in fruiting shoots and, for the first time, on quality variables of ‘Franquette’ walnuts harvested at two harvests, early and late, 43 and 84 d after treatment, respectively. Girdling was conducted on a part of four-year old branches at the onset of kernel growth. At late harvest, coinciding with commercial harvest, girdling advanced the mature fruit percentage, kernel weight, and oil content, whereas decreased kernel moisture and slightly affected the color brightness, although kernels remained with an extra light color. Advanced maturation increased linoleic acid and polyunsaturated fatty acid (PUFA) fraction in oil, whereas it decreased palmitic acid and the saturated fatty acid (SFA) fraction in oil, kernel total antioxidants, and Sols (sucrose, glucose, fructose) in kernels and leaves and leaf photosynthesis (Pn), whereas girdling had no effect on these variables. Oil rancidity remained stable throughout the experiment. Development of callus was observed on tree wounds 84 d after treatment. Conclusively, girdling enhanced the fruit maturation, resulting in higher uniformity of maturity and increased oil yield with no quality deterioration or apparent tree damage.

Detection of QTNs for kernel moisture concentration and kernel dehydration rate before physiological maturity in maize using multi-locus GWAS

Maize is China’s largest grain crop. Mechanical grain harvesting is the key technology in maize production, and the kernel moisture concentration (KMC) is the main controlling factor in mechanical maize harvesting in China. The kernel dehydration rate (KDR) is closely related to the KMC. Thus, it is important to conduct genome-wide association studies (GWAS) of the KMC and KDR in maize, detect relevant quantitative trait nucleotides (QTNs), and mine relevant candidate genes. Here, 132 maize inbred lines were used to measure the KMC every 5 days from 10 to 40 days after pollination (DAP) in order to calculate the KDR. These lines were genotyped using a maize 55K single-nucleotide polymorphism array. QTNs for the KMC and KDR were detected based on five methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, and ISIS EM-BLASSO) in the package mrMLM. A total of 334 significant QTNs were found for both the KMC and KDR, including 175 QTNs unique to the KMC and 178 QTNs unique to the KDR; 116 and 58 QTNs were detected among the 334 QTNs by two and more than two methods, respectively; and 9 and 5 QTNs among 58 QTNs were detected in 2 and 3 years, respectively. A significant enrichment in cellular component was revealed by Gene Ontology enrichment analysis of candidate genes in the intervals adjacent to the 14 QTNs and this category contained five genes. The information provided in this study may be useful for further mining of genes associated with the KMC and KDR in maize.

Examination of the Peleg and Normand equation during relaxation of wheat: The effect of holding time.

In this study, we analyzed the effect of the duration of relaxation experiments on the parameters of the model proposed by Peleg and Normand. The relaxation experiments were conducted for individual intact wheat kernels in compression. Single kernels were initially loaded with a force of 20 N, then maintained at a constant deformation over time of 300 s. For the following time intervals 0-10, 0-20, 0-30, 0-40, 0-50, 0-60, 0-120, 0-180, 0-240, and 0-300 s coefficients k1 , k2 and Y(t) were determined according to the Normand and Peleg equation. The effect of time was compared at variable wheat moisture ranging from 8 to 20%. For longer holding times, the relaxed force was higher and the decay parameter, Y(t), decreased. The coefficient k1 increased proportionally with increase in the time of relaxation from ~3.3 to 23.3 s. The values of coefficient k2 declined for longer experiments, and the decline was relatively quick for up to 60 s and then asymptotically diminished. The effect of time on the decay parameter Y(t) and coefficients k1 and k2 depended on the moisture of kernels. The accuracy of the models was significantly different for the studied holding times. The highest standard error of the estimate was evidenced for 10 s experiments, and its minimum was noted at times close to 120-180 s.

Development of effective drying strategy with a combination of radio frequency (RF) and convective hot-air drying for inshell hazelnuts and enhancement of nut quality

Drying characteristics of combined radio frequency (RF) and hot-air (HA) were investigated for inshell hazelnuts (Corylus avellana L.), which have air-gap between kernel and shell (shell, kernel, and air-gap between them). Inshell hazelnuts were subjected to HA, HA followed by RF (HAFRF), RF followed by HA (RFHA), and HA assisted RF (HARF) drying (simultaneous process). Fiber optic sensors were used to monitor temperature profiles for both hazelnut kernels and shells at three representative locations (center, edge, and corner) in a tray in 6-kW 27.12-MHz RF system with or without HA (~75 °C). RF heating resulted in higher kernel temperature than shell and was effective to remove kernel moisture. When RF heating was applied during or before HA drying, energy efficiency, drying efficacy, and nut quality were enhanced. This study provided a better understanding of drying characteristics of combined RF and HA process and suggested efficient RF-implemented drying strategies for inshell hazelnuts.

Enzymatic detoxification of the fumonisin mycotoxins during dry milling of maize

Fumonisin esterase FumD (EC 3.1.1.87), FUMzyme® (BIOMIN, Austria), effectively detoxifies fumonisin B mycotoxins (FB) by hydrolysis and removal of the tricarballylic acid groups. The current study evaluated FumD detoxification of total FB (FBT) in commercial maize utilising an experimental dry milling plant by introducing the enzyme during the kernel conditioning stage. Total FB and the hydrolysed product of FB1, HFB1, in maize and milling products were determined by LC-MS/MS. During maize conditioning of 4 h 10 min substantial FB1 hydrolysis was achieved between 1 and 4 U FumD/100 g maize. Complete conversion into HFB1 was delayed and only achieved at the highest enzyme concentration (32 U/100 g maize) reaching a 1:1 M conversion ratio. Dry milling of maize containing 3.29 ± 0.20 μmole FBT/kg (2354 ± 140 μg/kg) in the absence of FumD, resulted in a 2.5-fold increase in the FBT concentration in total hominy feed (8.34 ± 0.22 μmol/kg) (5979 ± 158 μg/kg) compared to the levels that prevail in Super (0.52 ± 0.07 μmol/kg) (347 ± 48 μg/kg) and Special (1.70 ± 0.01 μmol/kg) (1213 ± 8 μg/kg) maize meal, and Semolina (1.07 ± 0.14 μmol/kg) (765 ± 100 μg/kg) milling products. Introduction of FumD (40 U/kg) mainly impacted the total hominy feed product (germ + hominy milling fractions), constituting up to 30% of the reconstituted whole maize. A 99% reduction in FBT was obtained in total hominy feed, 48% in Semolina, 7% in Special maize meal, whereas no reduction was recorded in Super maize meal. FB1 reduction rates depend on the contamination level, kernel moisture and the diffusion rate from inner kernel layers to the kernel surface/aqueous interface. Risk modelling in children and adults indicated that FumD-treated whole maize and the resultant Semolina milling product intended for human consumption reduces the risk of exposure to FBT. However, no reduction in the exposure risk was observed when considering the Super and Special maize meal milling products. FB reduction in total hominy feed could open up new applications, such as its dietary incorporation as a source of fibre, minerals and bioactive plant constituents in maize-based food. In addition, the animal feed industry and subsistence maize farming communities using rudimentary milling processes, could also benefit.

The stability and variability of maize kernel moisture content at physiological maturity

AbstractMaize (Zea mays L.) kernel moisture content at physiological maturity significantly differs among hybrids and is affected by the environment. Nonetheless, 35% was previously reported and is widely accepted as the moisture content at physiological maturity. To verify whether the 35% moisture content could be applied to various hybrids and regions, a multi‐area, multi‐year trial was conducted from 2015 to 2018 in six locations in different maize‐planting regions of China. Time‐series kernel moisture contents and kernel dry weights were investigated for 156 hybrids in total to ascertain the growth pattern of the percentage maximum kernel dry weight as a function of kernel moisture content. The growth patterns were fitted with a tri‐linear model with a plateau, and at the point at which the percentage maximum kernel dry weight first reached its maximum (physiological maturity), the kernel moisture contents were 32% for summer maize, 34% for spring maize, and 38% for Daqing (a special spring maize region). We found that regional variation existed in kernel moisture content at physiological maturity. The regional average moisture content at physiological maturity could thus be used as an indicator to determine physiological maturity for most hybrids in the region. In addition, varietal differences in moisture content could be accounted for when using the regional average value.

Development and Performance Evaluation of a Small-scale Maize Harvester for Developing Countries

A small-scale maize harvester was designed and fabricated for developing countries and is composed of a harvester header, a chain conveyor, a drive power unit and a five-wheel tricycle. Fabrication of components was made and assembling of the devices on the tricycle was done. The performance evaluation of the small-scale maize harvester was done at 15% kernels moisture content (wet basis). Three rotational speeds of the engine, 1347, 1521 and 1937 rpm were used, while the forward velocity of the harvester was kept at an average of 0.617 km.hr-1. The testing experiment revealed significant effect of physical properties of maize (p<0,05). The highest machine capacity was obtained at 0.05 ha.hr-1, while the highest driving efficiency was 97.30% and the highest picking and conveying efficiencies were 84.11% and 98.21%, respectively. However, it was observed that the machine noise level decreased with increase in engine speed. Also, the engine speed affected both picking and conveying efficiencies. The designed machine is found suitable for most smallholder farms.

Combined linkage mapping and association analysis reveals genetic control of maize kernel moisture content.

The free moisture in crop kernels after being naturally dried is referred to as kernel moisture content (KMC). Maize KMC reflects grain quality and influences transportation and storage of seeds. We used an IBM Syn10 DH maize population consisting of 249 lines and an association panel comprising 310 maize inbred lines to identify the genetic loci affecting maize KMC in three environments. Using the IBM population detected 13 QTL on seven chromosomes, which were clustered into nine common QTL. Genome-wide association analysis (GWAS) identified 16 significant SNPs across the 3 environments, which were linked to 158 genes across the three environments. Combined QTL mapping and GWAS found two SNPs that were located in two of the mapped QTL, respectively. Twenty-three genes were linked with the loci co-localized in both populations. Of these 181 genes, five have previously been reported to be associated with KMC or to regulate seed development. These associations were verified by candidate gene association analysis. Two superior alleles and one favorable haplotype for Zm00001d007774 and Zm00001d047868 were found to influence KMC. These findings provide insights into molecular mechanisms underlying maize KMC and contribute to the use of marker-assisted selection for breeding low-KMC maize.

Predicting Kernel Growth of Maize under Controlled Water and Nitrogen Applications

The availability of water and nitrogen (N) to maize during its flowering stage affects the growth of individual kernels. The present study reports the variability of maize kernel dry weight under different levels of water and N applications. Two consecutive-year experiments were conducted during 2009 and during 2010 to study the interaction between three irrigation regimes and five N application rates on weekly maize kernel growth. Logistic and regression equations were fitted to kernel moisture content and kernel dry weight as a function of thermal time (TT) during critical crop stages. Kernel moisture content and growth rate increased non-linearly from 1 week after silking to physiological maturity. By applying logistic function we were able to improve simulation of kernel moisture content and daily increases in kernel dry weight. The logistic curve showed kernel moisture contents linearly correlated with kernel dry weight. Similarly, regression analyses of kernel dry weight showed a significant positive correlation with kernel moisture content for the 2009 (R2 = 0.86 NRMSE = 23%) and 2010 growing seasons (R2 = 0.92; NRMSE = 19%). Therefore, the logistics curves derived from the observed data may be helpful for predicting daily kernel growth for the semi-arid conditions. The results showed that the optimal N rate for maximum kernel dry weight was 250 kg ha−1 under 525 mm delta of water application ha−1. This rate might be considered in formulating good agricultural practices for optimum maize kernel growth in the semi-arid regions. Thus, our results contribute to better understanding of best management practices of N fertilizer and irrigation water for optimum maize productivity under semiarid region.

A Novel Handheld Device for Intact Corn Ear Moisture Content Measurement

Kernel moisture content is an important factor in mechanized corn harvesting. However, the rapid and nondestructive in situ detection of the kernel moisture content within an intact corn ear in the field remains challenging. In this work, we designed a novel handheld device with a double-ring sensing probe for nondestructive and convenient kernel moisture detection in intact corn ears based on an active reflection bridge operating in the radio frequency range. By proposing an equivalent first-order resistor-capacitor impedance model for a load composed of a corn ear and the double-ring sensing probe, we found that the reflection coefficient's phase angle $\theta $ was monotonic with the moisture content and also found that the measurement signal frequency affected the corn grain moisture measurement sensitivity. Before using the handheld device in the field, we investigated its optimal signal frequency range and the effects of temperature variations on the measurement results. In the frequency range of 140-165 MHz, the measured voltages from the device showed a good linear relationship and high sensitivity with respect to both the dielectric constants and the corn ear temperature (9 °C-22 °C). Using this device at a signal frequency of 160 MHz, we conducted corn ear moisture measurements in a total of 73 samples and then established a linear model. The results showed that, for corn ear moisture contents in the range of 15.7%-31.5%, the R values of the training set and the prediction set were 0.7027 and 0.8317, respectively, with a prediction error of 3.54% at the 95% confidence interval.

Influence of Blanching Time on Moisture, Sugars, Protein, and Processing Recovery of Sweet Corn Kernels

The objective of this work is to determine the influence of blanching time on moisture content, sugars, protein, and processing recovery (degree of cut corn) of sweet corn kernels. Sweetcorn cobs of the Jubilee variety were blanched in the water at the temperature 85 °C during the period of 2, 4, 6, and 8 min. Non-blanched cobs were used as control samples. Blanched cobs were made subject to a mechanical process of cutting-off the kernels. It was stated that the blanching time has significant statistical influence on the content of moisture, sugars, and protein in kernel as well as on the quantity of the cut-off kernel mass.

Calibration Algorithm for Rapid and Nondestructive Moisture Sensing in In-Shell Nuts

A new calibration algorithm is presented for instantaneous and nondestructive determination of moisture contents of in-shell nuts and kernels from measurement of the dielectric properties of in-shell nuts at a single microwave frequency. The new calibration algorithm relies on the use of a density-independent function, expressed in terms of the dielectric properties, and the existence of a direct relationship between the in-shell nut oven moisture content and kernel oven moisture content. Results of measurement by using a microwave moisture sensor operating at 5.8 GHz are presented, and kernel moisture calibration equations are established for peanuts and almonds.

Decreased Kernel Moisture in Medium‐Maturing Maize Hybrids with High Yield for Mechanized Grain Harvest

ABSTRACTKernel moisture influences harvest timing and the consequent mechanized harvest of maize (Zea mays L.). To decrease kernel moisture, growth season (the period from sowing to physiological maturity) was usually shortened for new hybrids in China, which also resulted in lower yield. Our objective was to understand the underlying mechanism to achieve both high grain yield and low grain moisture simultaneously for new hybrids. Field experiments were conducted in 2017 and 2018 in North China Plain with three different hybrids (ZD958 as the traditional hybrid, JNK728 and DK517 as the new hybrids, and XY335 as the transitional hybrid) under three densities (60,000, 75,000, 90,000 plants ha−1). For new hybrids, growth season was 9 to 12 d shorter than for other hybrids. Under the density of 60,000 plants ha−1, grain yield of new hybrids was 9.1% lower compared with the traditional and transitional hybrids. When the density was increased to 75,000 plants ha−1, grain yield of new hybrids (12.9 Mg ha−1) was similar or even higher. Grain moisture at physiology maturity averaged 272 g kg−1 for new hybrids, similar to the transitional hybrid and 7.5% lower compared with the traditional hybrid. The lower grain moisture mainly resulted from >30% of stover dry matter translocated to grain for new hybrids, similar to the transitional hybrid and 235.0% greater than the traditional hybrids. Furthermore, higher translocation rate was mainly from stalk in late grain‐filling stage. Our study highlighted the importance of yield improvement and the relationship between kernel moisture and dry matter translocation for new hybrids.

Relationships between transparency, amylose content, starch cavity, and moisture of brown rice kernels

Rice with low amylose content (AC) is popular due to the unique eating and cooking quality, but its transparency is poor. It is unclear why low AC rice has poor transparency until now. In this study, the transparency and microstructure of brown rice kernels were investigated in rices with different ACs. Chalkiness of endosperm resulted from the loosely packed starch granules, and existed in rice kernels with low and high moisture. However, dry kernels with low AC were opaque or dull due to the cavities in the center of starch granules, and could become transparent gradually with the increase of moisture. For rices with the same genetic background but different ACs, the cavity size was negatively correlated with AC, and the transparency of dry kernels was significantly correlated positively with AC and negatively with cavity size. The transparency of kernels was positively correlated with moisture of kernel, and the effect of moisture on transparency was significantly correlated positively with starch cavity size and negatively with kernel AC. The above results showed that the transparency of low AC rice was remarkably influenced by cavity size and AC of starch, and could be regulated through controlling the moisture of kernel.

Optimum plant density for crowding stress tolerant processing sweet corn

Globally, gains in sweet corn [Zea mays L.var. rugosa (or saccharata)] are a fraction of the yield advances made in field corn (Zea mays L.) in the last half-century. Grain yield improvement of field corn is associated with increased tolerance to higher plant densities (i.e., crowding stress). Processing sweet corn hybrids that tolerate crowding stress have been identified; however, such hybrids appear to be under-planted in the processing sweet corn. Using crowding stress tolerant (CST) hybrids, the objectives of this study were to: (1) identify optimum plant densities for a range of growing conditions; (2) quantify gaps in production between current and optimum plant densities; and (3) enumerate changes in yield and ear traits when shifting from current to optimum plant densities. Using a CST shrunken-2 (sh2) processing sweet corn hybrid, on-farm plant density trials were conducted in thirty fields across the states of Illinois, Minnesota and Wisconsin, from 2013 to 2017 in order to capture a wide variety of growing conditions. Linear mixed-effects models were used to identify the optimum plant density corresponding to maximum ear mass (Mt ha-1), case production (cases ha-1), and profitability to the processor ($ ha-1). Kernel moisture, indicative of plant development, was unaffected by plant density. Ear traits, such as ear number and ear mass per plant, average ear length, and filled ear length declined linearly with increasing plant density. Nonetheless, there was a large economic benefit to the grower and processor by shifting to higher plant densities in most environments. This research shows that increasing plant densities of CST hybrids from current (58,475 plants ha-1) to optimum (73,075 plants ha-1) could improve processing sweet corn green ear yield and processor profitability on average of 1.13 Mt ha-1 and $525 ha-1, respectively.

A Comparative Study of Genetic Diversity, Heritability and Inter-relationships of Tree and Nut Attributes between Prunus scoparia and P. elaeagnifolia using Multivariate Statistical Analysis

By applying multivariate statistical analysis, this research aimed to estimate the heritability and find relationships between the vegetative and reproductive characteristics of Prunus scoparia and Prunus elaeagnifolia. Twenty genotypes of each species were selected randomly from cultivated populations and twenty-two traits including the tree, leaf, flower, nut and kernel attributes were measured. Results showed that there were high levels of genotypic and phenotypic variations among the genotypes of both species. Many of the measurements pertaining to the leaf, flower, nut and kernel, showed very high heritability (H2 >90%) in both species, whilst some traits such as shoot diameter in P. scoparia and kernel moisture in both species had very lower heritability (H2 <50%). Generally, the heritability of measured traits in P. elaeagnifolia were higher than those of P. scoparia, especially foreconomically important traits including yield (H2 = 94 and H2 = 54.61, respectively in P. elaeagnifolia and P. scoparia), nut weight (H2 = 97.83 and H2 = 85.39.61, respectively in P. elaeagnifolia and P. scoparia) and oil percentage (H2 = 75.55 and H2 = 61.43, respectively in P. elaeagnifolia and P. scoparia). Stepwise regression analysis revealed that the most influential factors on yield of P. scoparia, were the fruit set, flower diameter and leaf length, whilst for the P. elaeagnifolia, the yield was mostly determined by fruit set and leaf area. The high genetic diversity and heritability of the studied traits, indicates high genetic potential of this germplasm to be utilized in future breeding programs.

Dynamics of the particle moisture distribution during storage of wheat under laboratory and pilot-scale conditions

To predict the storability of grain, detailed information is required on the moisture distribution within the grain bulk since a significant variance can be expected in the moisture content between individual grain kernels during storage. Therefore, it is important to consider and determine the single kernel moisture content distribution. The aim of this work was to investigate mass transfer processes that occur during long-term and intermediate storage of grain. For it, the method of particle moisture distribution analysis by means of the Time Domain Nuclear Magnetic Resonance spectroscopy was used. For this purpose, fundamental laboratory-scale experiments were conducted in small storage containers. As these storage experiments revealed, the width of the particle moisture distribution decreased noticeably when there was enough air available in the container for moisture exchange. Thereafter, the storage experiments were extended to pilot-scale using barrels to store grain for months in the scope of about 90 kg per batch. These experiments were performed without ventilation so as to simulate dead zones of airflow that often occur under industrial-scale flat storage conditions. In the closed barrels, no equalization of the particle moisture content was observed even after eleven months of storage. The knowledge gained from the experiments conducted at the micro and meso levels facilitates the understanding of the mass transfer processes that occur during macro scale storage, which are difficult to examine as an entity.

A PCB Sensor for Status Monitoring of Stored Food Stocks

Cereal grains are important food stocks that can be safely stored for long periods of time if stored at an appropriate temperature and moisture content. As such, they are of considerable interest for long-duration manned space missions. However, if exposed to moisture, the grains will imbibe water and begin to germinate, spoil, or become contaminated by the propagation of various microorganisms, such as fungi. Imbibed moisture can be detected capacitively, since the relative permittivity of water is much higher than the relative permittivity of organic materials. Since grains such as corn kernels are relatively large compared to the size of traditional microsensors, a printed circuit board capacitive fringing field sensor was developed to detect the imbibed moisture in corn kernels through measuring the resulting increase in capacitance. Sets of corn seed of varying moisture content were obtained and evaluated with the sensor. The results were compared with measurements from a commercially available grain moisture content tester and demonstrated a linear increase in sensor capacitance as a function of kernel weight and moisture content.