摘要
样品代表性是确保检测结果真实性和准确性的前提,以无人化检测应用场景为研究对象,通过对已有无人化扦样装置样品处理中主要重金属含量检测的样品均匀性研究,明确混匀操作和控制取样量是确保样品具有代表性的必要环节。采用染色模拟和实际样品验证相结合的方式,对自动化扦取样品的混匀操作方式和参数,样品粉碎后取样量和测试用样品量等关键参数进行系统研究,获得一套保障无人化重金属检测样品代表性的最优混匀取样方案,结果表明:采用锚式山型桨以公转方式搅拌100圈或者反复混合分样3次,粉碎用最小样品取样量为150 g;样品最大粉碎粒径为1 mm,最小称样量为0.5 g。该方案适合混匀6 kg及以下稻谷、小麦样品中铅、镉元素的代表性检测,研究结果为确保粮食实现无人化重金属检测结果的代表性和准确性提供技术支撑。
Sample representativeness is the premise to ensure the authenticity and accuracy of test results.The application scenario of unmanned detection is taken as the research object.Through the research on the uniformity of major heavy metals content detection in the sample processing of unmanned sample sampler,it is clear that mixing operation and sampling control are the necessary steps to ensure the representativeness of samples.By the method of combining dyeing simulation and actual sample verification,the key parameters such as the blending operation mode and parameters,the amount of samples crushed and tested for automatic sampling were systematically studied,and an optimal blending sampling scheme was obtained to ensure the representativeness of samples for unmanned heavy metal testing.The results showed that,the anchor type mountain paddle was used to stir 100 laps in revolution mode or repeat mix and separate samples for 3 times,and the minimum sample sampling amount for crushing was 150 g.The maximum crushed particle size of the sample was 1 mm and the minimum weight was 0.5g.This scheme was suitable for the representative detection of lead and cadmium elements in rice and wheat samples less than 6 kg.The research results provide technical supports for ensuring the representativeness and accuracy of heavy metal detection results in grain.
作者
张洁琼
周明慧
李丽
杨鸣赫
王松雪
ZHANG Jie-qiong;ZHOU Ming-hui;LI Li;YANG Ming-he;WANG Song-xue(Cereals and Oils Quality and Safety Research Institute,Academy of National Food and Strategic Reserves Administration,Beijing 100037,China)
出处
《粮油食品科技》
CAS
CSCD
2023年第4期111-117,共7页
Science and Technology of Cereals,Oils and Foods
基金
中央级公益性基本科研业务费专项(JY2204)。
关键词
无人化检测
粮食
重金属
样品代表性
unmanned detection
grain
heavy metal
representativeness of samples