Measuring grain characteristics is an integral component of cereal breeding and research into genetic control of seed development. Measures such as thousand grain weight are fast, but do not give an indication of variation within a sample. Other methods exist for detailed analysis of grain size, but are generally costly and very low throughput. Grain colour analysis is generally difficult to perform with accuracy, and existing methods are expensive and involved.
We have developed a software method to measure grain size and colour from images captured with consumer level flatbed scanners, in a robust, standardised way. The accuracy and precision of the method have been demonstrated through screening wheat and Brachypodium distachyon populations for variation in size and colour.
By using GrainScan, cheap and fast measurement of grain colour and size will enable plant research programs to gain deeper understanding of material, where limited or no information is currently available.
Grain (or seed) size is an important component of both basic plant research, since seed formation and development is a fundamental aspect of plant reproduction, and cereal breeding, as a component of yield and vigour. Existing methods of determining seed size tend to either favor speed of measurement while sacrificing resolution, or are so involved that high throughput measurement is challenging. In the context of cereal breeding, seed weight is an important trait related to seed size, and therefore measuring the weight of a standard number or volume of seeds is practical and informative. Measures such as thousand-grain weight or hectolitre weight are commonly used since they are fast, and not prone to error. However, they give no measure of variation within a sample. Detailed measurement of seed shape characteristics such as length and width traditionally depends on laborious techniques such as manual measurement of individual seeds . The single kernel characterization system (SKCS, ) is a relatively low throughput, destructive technique that measures hardness as well as seed size. Systems such as SeedCount (Next Instruments, NSW, Australia) utilize image analysis to give measures of size for individual seeds within a sample, allowing for a detailed understanding of variation, as well as an accurate estimation of the sample mean. However the time required for sample preparation especially for large numbers of samples (SeedCount samples need to be placed in wells in a sample tray), along with the initial cost of such systems can be prohibitive (~ $AUD15000).
Accurate, widely interpretable measurement of colour is technically challenging, and a field unfamiliar to many biologists. Because perception of colour is affected by the environment in which it is observed, standardised measurement is critical. Such a requirement generally involves somewhat laborious sample preparation and high cost analytical equipment. Chroma meters are standard tools for accurate colour determination in many industries, and can be applied to cereal products along the processing chain, including grain, flour, dough and the final processed product. For standardised, comparable colour measurements, chroma meters measure in the CIELAB colour space, a device independent colour space which includes all perceivable colours. CIELAB is made up of three channels: L*, which ranges from 0 to 100 and represents the lightness of the colour; a*, negative or positive values of which represent green or magenta, respectively; and b*, representing blue (negative) or yellow (positive). These channels can then be used individually to quantify specific colour attributes, which may be linked to biological factors . While the measurements given by chroma meters are highly controlled and standardised, when applied to grain, there are several drawbacks. Because of the small area that is measured, only a limited number of grains are visible by the observer, and a single average value is reported. This, therefore, provides no information regarding variation within a sample of grain. An alternative method is the SeedCount system, which also provides colour information based on the CIELAB colour space, as well as other grain characteristics such as size and disease state.
Here, we present GrainScan , a low cost, high-throughput method of robust image capture and analysis for measurement of cereal grain size and colour. GrainScan utilizes reflected light to accurately capture colour information described in a device independent colour space (CIELAB), allowing comparison of colour data between scanning devices.
Traits measured for B.distachyon seeds were area, perimeter, width and length. Despite the marked difference in shape between seeds from wheat and B. distachyon, GrainScan successfully identified seeds, and allowed estimation of mean size as well as variation within a sample (Figure 4, Table 5). The distributions of grain size suggested the possibility of bimodality in these samples, although the sample sizes were much lower than those for wheat. Because of the reduced number of seeds per image, standard errors were higher than those for wheat, highlighting the benefit of scanning larger number of seeds. Since GrainScan can accurately measure seed size across two species with largely differing seed shapes, it is therefore likely that GrainScan can be successfully implemented for many different plant species that also have regular, approximately elliptical morphology.
GrainScan enables robust, standardized and detailed study of grain size, shape and colour at very low cost and relatively high throughput. We have demonstrated that size measurements from GrainScan are reproducible between scans, agree well with accepted image analysis techniques, and result in similar rankings of sample material. Because of the dramatically lower cost, and higher throughput of GrainScan compared to other standardized colour measurement methods, GrainScan facilitates detailed study of grain colour in large populations.
The software has two independent options in the analysis of colour. One option is to make the colour measurements for each grain in CIELAB values rather than the raw RGB values measured by the scanner. To use the colour calibration option, the image of a calibrated colour checker card must first be analysed using the ColourCalibration software. This software locates the card, segments each of the colour swatches, extracts the mean RGB values for each swatch, and determines the transformation matrix, RGB2Lab, by linear regression between the measured RGB values and the supplied CIELAB values for each swatch. For convenience, the transformation matrix is saved as two images, one containing the 3×3 matrix and one the 3x1 offset (with filename suffixes of *RGB2Labmat.tif and *RGB2Laboff.tif respectively). By inputting this transformation matrix into the GrainScan software, colour measurements made within each labelled grain can be converted from raw RGB values to calibrated L*, a*, and b* values.
Vibratory sieve shakers are frequently used for grain size analysis of cement clinker, chemicals, coffee, construction materials, fertilizers, fillers, flours, grains, metals powders, minerals, nuts, plastics, sand, seeds, soils, washing powder, etc.
Flowable, unagglomerated samples can be analyzed by using the X-Fall module. The measurement is non-destructive because the particles directly fall from a chute through the field of view. X-Fall is suitable for particle sizes up to 8 mm; the detection sensitivity for over-sized grains is extremely high. In contrast to dispersion by air pressure, the sample can be recovered after the measurement with X-Fall.
Abstract:In this paper, the effect of grain size and micromorphology of Cu foil on the velocity of the flyer of an exploding foil detonator was studied. A Cu foil with different grain sizes and micromorphologies was prepared by the physical vapor deposition sputtering method. The flyer velocity of the Cu foil was measured by the photon Doppler technique (PDT). The influence of the grain size and micromorphology of the Cu foil (which was the core transducer of the exploding foil detonator) on the flyer velocity and reacted morphology was discussed. The results show that the grain size and micromorphology of the Cu film can greatly affect the velocity and morphology of the flyer. The grain size of the Cu film is more uniform, and the stimulus response in the middle area of the bridge foil is more concentrated. In addition, the current density becomes more uniform, resulting in a better explosion performance. Consequently, the speed of the formed flyer becomes higher, leading to a smoother flyer surface, which is more conductive to energy conversion.Keywords: exploding foil detonator; copper foil; grain size; flyer morphology; flyer velocity
It has 2 trigger inputs to trigger 2 different samples, CV input assignable to any sound parameter, and signal OUTPUT. The CV input can also be used to trigger the grain shift. GrandPA reads microSD card accessible from the front panel and runs on the same sound core as microGranny 2. For each sample, you can adjust: sample rate, crush, grain size, shift speed, attack, release (full release is hold), start, and end position.
What does mesh size mean? Count the number of openings in one inch of screen (United States mesh size). The number of openings is the mesh size. So a 4-mesh screen means there are four little squares across one linear inch of screen. A 100-mesh screen has 100 openings, and so on. As the number describing the mesh size increases, the size of the particles decreases. Higher numbers equal finer material. Mesh size is not a precise measurement of particle size. Below you will find our mesh-to-micron calculator and if needed, you can also download a printable copy from the link below. Feel free to reach out to us for any of your particle separation needs. Elcan has a full-scale contract manufacturing facility where we toll process high-end/high-value powders for companies around the world. 2b1af7f3a8