Crops ›› 2020, Vol. 36 ›› Issue (5): 170-173.doi: 10.16035/j.issn.1001-7283.2020.05.025

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Error Analysis of Moisture Content in Maize Seeds by Quick Water-Content Measuring Method

Yan Xiaoguang(), Du Yanwei, Li Hong(), Dong Hongfen, Li Aijun, Wang Guoliang, Zhou Nan   

  1. Shanxi Agricultural University (Shanxi Academy of Agricultural Sciences),Millet Research Institute, Changzhi 046011, Shanxi, China
  • Received:2020-02-11 Revised:2020-05-08 Online:2020-10-15 Published:2020-10-12
  • Contact: Li Hong E-mail:gzsyxg001@163.com;lih0910@163.com

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Abstract:

The total of thirty-seven mid-late maturity maize varieties from regional trials in Shanxi province were used as experimental materials. Corn moisture determination meter PM-8188-A was used to measure the moisture in kernel of maize at four different temperatures and the measured values were compared with those by the traditional standard oven drying method. Using regression analysis, the corresponding real water mathematical equations for the maize kernels were established. This mathematical model would minimized the measuring errors caused by the environmental temperature in the process of capacitive quick water-content in kernel of maize in the field. It has certain application value for the breeder to select maize varieties with low moisture content at harvest time. The results showed that the measured value of the capacitor express method tended to increase with the increase of temperature within the range of 10℃ to 25℃, and the minimum measured error value was at 20℃.

Key words: Maize, Grain moisture content, Different temperatures, Error

Table 1

The paired t-test results of quick measured water content and direct-drying methods at different temperatures"

温度Temperature (℃) 标准差Standard deviation 标准误Standard error 自由度df t值t-value P值P-value 相关系数Correlation coefficient
10 0.9333 0.1493 36 4.2233 0.0020** 0.9165
15 0.7753 0.1147 36 4.7318 0.0010** 0.9563
20 0.2390 0.0576 36 2.1213 0.0408* 0.9869
25 0.5218 0.0858 36 2.1737 0.0364* 0.9730

Fig.1

Regression curves of standard water content and quick measured water content at four temperature gradients"

Table 2

Regression models of quick and standard moisture values under the four temperature environments"

温度
Temperature (℃)		 模型Model y=ax2+bx+c
a b c R2
10 0.0370 -1.2882 33.8380 0.8536
15 0.0323 -0.9733 28.8920 0.9241
20 -0.0053 1.2578 -3.2026 0.9758
25 0.0096 0.5221 6.0521 0.9630
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