中国稻米营养元素区域尺度地理空间分布的原产地预测--粳稻溯源案例研究

IF 7.4 Q1 FOOD SCIENCE & TECHNOLOGY Food frontiers Pub Date : 2024-07-09 DOI:10.1002/fft2.445
Meiling Sheng, Chunlin Li, Weixing Zhang, Jing Nie, Hao Hu, Weidong Lou, Xunfei Deng, Shengzhi Shao, Xiaonan Lyu, Zhouqiao Ren, Karyne M. Rogers, Syed Abdul Wadood, Yongzhi Zhang, Yuwei Yuan
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摘要

要对中国大米进行有效的地理产地判别,需要一个庞大的样本数据库,以确保在区域范围内有足够的数据进行产地验证。本研究利用环境相似性建立了水稻营养元素空间数据库,然后利用反向传播人工神经网络建模(BPNN)验证了数据库的有效性。首次利用环境相似性方法建立了 14 种水稻营养元素(Al、Ba、Ca、Cu、Cr、Fe、K、Mg、Mn、Mo、Na、Ni、Rb 和 Zn)在区域尺度上的空间分布模型。利用 692 个样品的元素浓度建立了中国东北(N-E)、长江中下游平原(Y-R)、西南(S-W)和东南(S-E)的模拟地理起源预测模型。结果表明,根据各地区均方根误差(RMSE)的最小排序,环境相似性模型在这四个产区的性能表现为 S-W > N-E > S-E > Y-R。例如,S-W、N-E、S-E 和 Y-R 地区锌的均方根误差分别为 2.0、2.4、2.7 和 3.7 毫克/千克。一项关于粳稻溯源性的案例研究表明,使用 BPNN 模型,模拟数据库对粳稻的产地判别准确率(91.8%)高于实际数据库(87.0%)。这表明,模拟水稻元素数据库可以提高中国水稻地理原产地判别的准确性,并有可能应用于其他大型国家级农作物数据集。
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Predicting the geospatial distribution of Chinese rice nutrient element in regional scale for the geographical origin—A case study on the traceability of Japonica rice

Effective geographical origin discrimination of Chinese rice requires a large database of samples to ensure sufficient data for origin verification at a regional scale. In this study, environmental similarity was used to establish a spatial database of rice nutrient element, and then the validity of the database was verified using the back propagation artificial neural networks modeling (BPNN). The spatial distribution model of 14 rice nutrient element (Al, Ba, Ca, Cu, Cr, Fe, K, Mg, Mn, Mo, Na, Ni, Rb, and Zn) on regional scale was built using an environmental similarity method for the first time. Elemental concentrations of 692 samples were used to build a simulated geographical origin prediction model for northeastern (N-E), middle to lower Yangtze River plain (Y-R), southwestern (S-W), and southeastern (S-E) in China. The results indicated that the performance of the environmental similarity model for these four growing regions was S-W > N-E > S-E > Y-R based on the lowest ranking root mean square error (RMSE) for each region. For example, the RMSEs of Zn in S-W, N-E, S-E, and Y-R regions were 2.0, 2.4, 2.7, and 3.7 mg/kg, respectively. A case study on the traceability of Japonica rice was shown that Japonica rice could be discriminated with higher origin accuracy using a simulated database (91.8%) than by the actual database (87.0%) using the BPNN model. This indicates that a simulated rice element database could improve the accuracy of geographical origin discrimination for Chinese rice and potentially be applied to other large national-scale crop datasets.

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