岳伟, 陈曦, 曹强, 占新春, 阮新民, 徐建鹏, 郁凌华. 安徽省稻米气候品质评价方法[J]. 农业工程学报, 2022, 38(19): 102-109. DOI: 10.11975/j.issn.1002-6819.2022.19.012
    引用本文: 岳伟, 陈曦, 曹强, 占新春, 阮新民, 徐建鹏, 郁凌华. 安徽省稻米气候品质评价方法[J]. 农业工程学报, 2022, 38(19): 102-109. DOI: 10.11975/j.issn.1002-6819.2022.19.012
    Yue Wei, Chen Xi, Cao Qiang, Zhan Xinchun, Ruan Xinmin, Xu Jianpeng, Yu Linghua. Evaluating the climatic quality of rice in Anhui Province of China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(19): 102-109. DOI: 10.11975/j.issn.1002-6819.2022.19.012
    Citation: Yue Wei, Chen Xi, Cao Qiang, Zhan Xinchun, Ruan Xinmin, Xu Jianpeng, Yu Linghua. Evaluating the climatic quality of rice in Anhui Province of China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(19): 102-109. DOI: 10.11975/j.issn.1002-6819.2022.19.012

    安徽省稻米气候品质评价方法

    Evaluating the climatic quality of rice in Anhui Province of China

    • 摘要: 为科学评价区域稻米气候品质提供技术支撑,该研究基于2008—2018年安徽省区域性试验稻米品质资料及对应站点气象数据,采用数理统计方法,明确了稻米品质形成关键期和最佳温度,建立了中籼和中粳稻米气候品质评价模型,并利用2018年分期播种试验稻米品质资料对模型进行验证。结果表明:中籼和中粳稻米品质形成关键期分别为齐穗后33 d和36 d,稻米品质形成的适宜温度分别为24.8 ℃和23.0 ℃。将稻米气候品质划分为“特优”“优”“良好”“一般”4个等级,对应中籼稻米气候品质指数(IACQ)范围分别为:IACQ≥3.40、3.09≤IACQ<3.40、2.73≤IACQ<3.09、IACQ<2.73,中粳稻米气候品质指数范围分别为:IACQ≥3.36、3.08≤IACQ<3.36、2.68≤IACQ<3.08、IACQ<2.68。经验证,与实际等级相比,模型计算得到的中籼和中粳稻米气候品质等级准确率均为80%。该研究建立的评价模型可用于中籼和中粳稻米的气候品质评价工作。

       

      Abstract: Environment conditions have been the most important influencing factors on the rice quality. It is a high demand to determine the positive or negative influences of the climate and weather on the rice quality, in order to effectively improve the added value and market competitiveness of rice. In this study, an evaluation model of rice climatic quality was established to provide the theoretical basis and technical support for the evaluation of the climatic influences on in Anhui Province of China. The key period and optimum temperature were clarified for the formation of rice climatic quality. Then, the rice climatic quality and comprehensive meteorological condition index were constructed using the rice quality data from the regional trials of three sites in the Hefei, Chuzhou, and Fengtai City in Anhui Province of China. Taking the mid-season indica and japonica rice as research objects, the daily meteorological observation data was collected from 2008 to 2018. The weighted summation and computer numerical simulation were carried out to preprocess the rough data. Finally, an evaluation model was established for the climatic quality of rice using regression analysis. The optimal model was then validated using the rice quality data from the sowing experiment by the stages in 2008. The results showed that the six indexes of climatic quality were achieved, including the percentage of head rice, chalkiness, transparency, alkali spreading value, gel consistency, and amylose content. The comprehensive index of meteorological conditions was obtained after the numerical simulation of three elements (average temperature, radiation, and diurnal temperature range). The key periods and optimum temperatures of climatic quality formation were 33 and 36 days after the date of full heading stage, while 24.8℃ and 23.0℃ for the mid-season indica rice and mid-season japonica rice, respectively. Four grades were divided into the "Extra excellent", "Excellent", "Good", and "General" for the climatic quality of the mid-season indica and japonica rice. Therefore, the climatic quality index larger than 3.40 was matched with the "Extra excellent" grade of indica rice. The "Excellent" grade was matched between 3.09 and 3.40, while the "Good" grade was in the range between 2.73 and 3.09. At last, the climatic quality index smaller than 2.73 was matched with the "General" grade of indica rice. Similarly, the climatic quality index for the japonica larger than 3.36 was matched with the "Extra excellent" grade. Specifically, the ranges between 3.08 and 3.36, 2.68 and 3.08, and smaller than 2.68 were matched with the "Excellent", "Good", and "General" grades, respectively. The model validation showed that the 80% accuracy of climatic quality was achieved in the mid-season indica and japonica rice. The climatic quality grade was mainly one grade lower than the actual one. The difference between the climatic and the actual quality of rice was attributed to the different evaluation indices and impact factors. Therefore, the climatic quality of rice can be expected to serve as an excellent indicator of the actual quality. In summary, the climatic quality of rice can be evaluated by meteorological factors, such as the average temperature, radiation, and diurnal temperature range during the rice growth period. The improved evaluation model can also be used to evaluate the climatic quality of mid-season indica and japonica rice.

       

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