Prediction of Wisconsin Tester Breakage Susceptibility of Corn from Bulk Density and NIRS Measurements of Composition

Siska, Juraj; Hurburgh, Charles R.

doi:10.13031/2013.28244

Cited by 11 publications

(3 citation statements)

References 5 publications

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“…When the BS is at maximum value, the maize kernels show higher mechanical crushing resistance. The change rules of BS of maize kernels obtained by HANDY are similar to those obtained by using the Stein Crush resistance tester, Wisconsin Tester, and Centrifugal Corn Crush resistance tester in previous studies [27][28][29][30].…”

Section: Repeatability Of Resultssupporting

confidence: 79%

HANDY: a device for assessing resistance to mechanical crushing of maize kernel

Su¹,

Xu²,

Cui

et al. 2020

Preprint

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Background: How to control the physical damage during maize kernel harvesting is a major problem for both mechanical designers and plant breeders. A limitation of addressing this problem is lacking a reliable method and model for assessing the relation between kernel damage susceptibility and threshing quality. The design, construction, and testing of a portable tool called “HANDY”, which can assess the resistance to mechanical crushing in maize kernel. HANDY can impact the kernel with a special accelerator at a given rotating speed and then cause measurable damage to the kernel. These factors are varied to determine the ideal parameters for operating the HANDY. Results: Baseline testing of the HANDY is performed to determine the initial range of testing parameters. The result shows that the optimum number of test times is one. Breakage index (BI, target index of HANDY), decreased as the moisture content of kernel increased or the rotating speed decreased within the tested range. Furthermore, the HANDY exhibited a greater sensitivity in testing kernels at higher moisture level influence on the susceptibility of damage kernel than that in Breakage Susceptibility tests, particularly when the centrifugation speed is about 1800 r/min and the centrifugal disc type is curved. Considering that the mechanical properties of kernels vary greatly as the moisture content changes, a subsection linear (average goodness of fit is 0.9) to predict the threshing quality is built by piecewise function analysis, which is divided by kernel moisture. Specifically, threshing quality is regarded as a function of the measured result of the HANDY. Five maize cultivars are identified with higher damage resistance among 21 tested candidate varieties. Conclusions: The HANDY provides a quantitative assessment of the mechanical crushing resistance of maize kernel. The BI is demonstrated to be a more robust index than breakage susceptibility (BS) when evaluating threshing quality in harvesting in terms of both reliability and accuracy. This study also offers a new perspective for evaluating the mechanical crushing resistance of grains and provides technical support for breeding and screening maize varieties that are suitable for mechanical harvesting.

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Section: Repeatability Of Resultssupporting

confidence: 79%

HANDY: a device for assessing resistance to mechanical crushing of maize kernel

Su¹,

Xu²,

Cui

et al. 2020

Preprint

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show abstract

“…Two main tests have been used to measure breakage and its relationship to hardness. The main breakage tester is the Wisconsin Breakage tester, with a number of reports detailing the effects on hardness prior to and after being tested in the breakage tester − . A number of factors affect breakage including temperature, moisture, genetics, growing environment, and hardness.…”

Section: Processingmentioning

confidence: 99%

Hardness Methods for Testing Maize Kernels

Fox

Manley

2009

J. Agric. Food Chem.

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Maize is a highly important crop to many countries around the world, through the sale of the maize crop to domestic processors and subsequent production of maize products and also provides a staple food to subsistance farms in undeveloped countries. In many countries, there have been long-term research efforts to develop a suitable hardness method that could assist the maize industry in improving efficiency in processing as well as possibly providing a quality specification for maize growers, which could attract a premium. This paper focuses specifically on hardness and reviews a number of methodologies as well as important biochemical aspects of maize that contribute to maize hardness used internationally. Numerous foods are produced from maize, and hardness has been described as having an impact on food quality. However, the basis of hardness and measurement of hardness are very general and would apply to any use of maize from any country. From the published literature, it would appear that one of the simpler methods used to measure hardness is a grinding step followed by a sieving step, using multiple sieve sizes. This would allow the range in hardness within a sample as well as average particle size and/or coarse/fine ratio to be calculated. Any of these parameters could easily be used as reference values for the development of near-infrared (NIR) spectroscopy calibrations. The development of precise NIR calibrations will provide an excellent tool for breeders, handlers, and processors to deliver specific cultivars in the case of growers and bulk loads in the case of handlers, thereby ensuring the most efficient use of maize by domestic and international processors. This paper also considers previous research describing the biochemical aspects of maize that have been related to maize hardness. Both starch and protein affect hardness, with most research focusing on the storage proteins (zeins). Both the content and composition of the zein fractions affect hardness. Genotypes and growing environment influence the final protein and starch content and, to a lesser extent, composition. However, hardness is a highly heritable trait and, hence, when a desirable level of hardness is finally agreed upon, the breeders will quickly be able to produce material with the hardness levels required by the industry.

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“…Liang et al [22] developed a threshing model and found that combine performance could be improved by analyzing and optimizing the structure and variables of the threshing unit. Siska and Hurburgh [23] developed the corn breakage prediction model using multiple linear regression techniques, with R 2 of 0.65. Additionally, Maertens et al [24] , Maertens and De Baerdemaeker [25] and Miu and Kutzbach [26] forecasted the characteristics of the material moving inside combine harvesters.…”

Section: Introduction mentioning

confidence: 99%

Selection of proper combine harvesters to field conditions by an effective field capacity prediction model

Doungpueng

Saengprachatanarug

Posom

et al. 2020

International Journal of Agricultural and Biological Engineering

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Farmers have to finish their harvesting with high efficiency, because of time and cost. However, farmers are lacking knowledge and information required for selecting suitable combine harvesters and giving the conditions of their rice fields, because both information factors (combine harvester and field condition) impact the field capacity. The field capacity model was generated from combine harvesters with the Thai Hom Mali rice variety (KDML-105). Therefore, this study aimed to determine the prediction model for effective field capacity to combine harvesters when harvesting the Thai Hom Mali rice variety (KDML-105). The methods began by collecting data of 15 combine harvesters, such as field, crop, and machine conditions and operating times; to generate the prediction model for the KDML-105 variety. The prediction model was then validated using 12 combine harvesters that were collected similarly to the model creation. The results showed a root mean square error (RMSE) of 0.24 m 2 /s for the model. The prediction model can be applied for farmers to select the proper combine harvesters and give their field conditions.

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Prediction of Wisconsin Tester Breakage Susceptibility of Corn from Bulk Density and NIRS Measurements of Composition

Cited by 11 publications

References 5 publications

HANDY: a device for assessing resistance to mechanical crushing of maize kernel

HANDY: a device for assessing resistance to mechanical crushing of maize kernel

Hardness Methods for Testing Maize Kernels

Selection of proper combine harvesters to field conditions by an effective field capacity prediction model

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