Graham-Acquaah S, Mauromoustakos A, Cuevas R P, Manful J T
1University of Arkansas, Fayetteville, AR USA.
4Africa Rice Center (AfricaRice), Cotonou, Benin.
J Food Sci Technol. 2020 Apr;57(4):1505-1516. doi: 10.1007/s13197-019-04186-7. Epub 2019 Nov 30.
Rice consumers in West Africa (WA) have an acquired preference for imported rice. Enhancing consumption of local rice requires matching the grain quality attributes of the imported benchmarks in addition to increasing productivity of local rice cultivars. Thus, there is a need to develop screening tools that will aid breeding programs select for high-yielding and stress-tolerant cultivars whose grain quality are at par with imported rice. Hence, this study evaluated various grain quality characteristics of 316 commercial milled rice samples from urban markets in three WA countries (Benin, Cameroon, and Ghana) and developed linear discriminant models (LDAs) to classify rice according to their origins and to predict the imported rice classification of local germplasm based on their grain quality attributes. More than half of the commercial rice samples that were collected originated from Thailand (60%); in contrast, only a small fraction was locally grown (2%). The commercial rice from different origins were distinguishable based on the quality attributes evaluated, contributing to the relatively high classification rates achieved by the fitted LDAs. These results indicate that multivariate models could be useful during varietal improvement as tools for screening for cultivars that can match the quality of imported rice.
西非的大米消费者已养成对进口大米的偏好。要增加本地大米的消费量，除了提高本地水稻品种的产量外，还需要使其谷物品质特性与进口基准相匹配。因此，需要开发筛选工具，以帮助育种计划选择高产且耐胁迫的品种，其谷物品质与进口大米相当。因此，本研究评估了来自西非三个国家（贝宁、喀麦隆和加纳）城市市场的316个商业碾米样品的各种谷物品质特征，并开发了线性判别模型（LDA），以便根据大米的产地对其进行分类，并根据本地种质的谷物品质属性预测其进口大米类别。所采集的商业大米样品中，超过一半来自泰国（60%）；相比之下，本地种植的仅占一小部分（2%）。根据所评估的品质属性，不同产地的商业大米是可区分的，这使得拟合的LDA能够实现相对较高的分类率。这些结果表明，多变量模型在品种改良过程中作为筛选能够与进口大米品质相匹配的品种的工具可能会很有用。
