Crops ›› 2023, Vol. 39 ›› Issue (6): 108-113.doi: 10.16035/j.issn.1001-7283.2023.06.015

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Research on the Construction Strategy of Maize Grain Dehydration Model in Cold Northeast China

Wu Qi1(), Ming Bo2, Gao Shang2, Yang Hongye2, Zhang Chuan1, Chu Zhendong1, Li Shaokun1,2()   

  1. 1Heilongjiang Bayi Agricultural University, Daqing 163000, Heilongjiang, China
    2Institute of Crop Sciences,Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2023-03-22 Revised:2023-04-24 Online:2023-12-15 Published:2023-12-15

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Abstract:

Constructing a model for dehydrating maize kernels is an important theoretical tool for investigating the dehydrating characteristics of various kernel variations and screening suitable mechanical grain harvesting types for cultivation areas. The cold Northeastern region is an important early-to-mid maturing cultivation of maize area, where rapid cooling and early frost in the fall, as well as low maturity and excessive moisture content of the kernels throughout the harvest season, are critical production concerns limiting maize industry development. During 2021-2022, a staged planting experiment was conducted in the cold Northeastern region on typical early-mid maturing maize varieties (Demeiya 1 and Demeiya 3) and the effects of shifting weather conditions on the drying process of maize kernels were simulated using various sowing treatments. The dehydrating model for the varieties was built using various modeling strategies, such as a full sowing dates and a portion sowing dates. The accuracy differences of the models were analyzed under various strategies, establishing a method for quickly building a dehydrating model for varieties. The results showed that the dehydration models built by various modeling techniques for Demeiya 1 and Demeiya 3 did not exhibit significant differences in model parameters or simulation precision, and the model parameter variability gradually decreased with the increase of the number of sowing dates. The models developed using different methods were assessed at three stations in the Northeastern spring corn region, and there was no apparent difference in the modeling accuracy. By employing phased sowing, a robust model for varieties could be constructed, with stable prediction accuracy between years and regions, accelerating the construction of maize variety dehydrating models, and provided a powerful theoretical tool for evaluating the suitability of mechanical grain harvesting for varieties.

Key words: Maize, Grain dehydration, Logistic Power model

Fig.1

Average daily temperature after spitting at test site in 2021-2022"

Table 1

"

品种
Variety		 年份
Year		 播期
Sowing
date		 播种日期
Planting
date		 吐丝期
Silking
date		 成熟日期
Maturity
date
德美亚1号
Demeiya 1		 2021 B1 05-06 07-16 08-17
B2 05-17 07-19 08-17
B3 05-27 07-24 09-13
2022 B1 05-07 07-15 08-24
B2 05-17 07-19 08-29
B3 05-27 07-24 09-14
德美亚3号
Demeiya 3		 2021 B1 05-06 07-16 08-29
B2 05-17 07-19 08-29
B3 05-27 07-27 09-23
2022 B1 05-07 07-19 09-03
B2 05-17 07-23 09-14
B3 05-27 07-29 09-23

Fig.2

Relationship between grain moisture content and days after silking in two varieties"

Fig.3

Fitting curves for seed moisture contents of varieties and comparison of predicted values with measured values of model"

Table 2

Comparison of parameters for different modeling conditions for different varieties"

品种Variety 建模播期数量Sowing date number for modeling a b R2 RMSE
德美亚1号Demeiya 1 2 790.83±29.00a 1.68±0.04a 0.92a 4.50a
3 788.00±18.00a 1.70±0.03a 0.90a 4.30a
4 797.00±15.00a 1.71±0.02a 0.90a 4.26a
全部 783.41±14.00a 1.67±0.03a 0.83b 4.19a
德美亚3号Demeiya 3 2 922.54±26.00a 1.87±0.04b 0.92a 5.43a
3 922.08±18.00a 1.89±0.05b 0.90a 5.15a
4 926.37±11.00a 1.91±0.02b 0.90a 4.62a
全部 937.06±9.00a 2.00±0.04a 0.86b 4.83a

Fig.4

Comparison of parameters of variety modeling and sowing date modeling box plots"

Fig.5

Comparison of predicted and measured seed moisture contents in different regions of Demeiya 1"

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