CN118518841B - A method for detecting pollutants in aquatic products - Google Patents
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Abstract
本发明涉及污染物检测技术领域,具体地公开了一种水产品中污染物的检测方法,包括:步骤一:对水产品进行检测,并对水产品污染物含量进行评估,生成污染物含量评估信号;步骤二:基于污染物含量异常信号,分析投喂目标饲料与水产品污染之间的关系,并生成投喂影响信号,从而便于分析投喂的目标饲料是否会对水产品的污染物含量产生影响;通过收集水产品的分泌物进行分析,无需破坏水产品样本,保证了水产品的完整性和安全性;通过了解饲料投喂对水产品污染物含量的影响后,养殖者可以根据实际情况调整饲料配方和投喂策略,选择更加环保、安全的饲料,或者改变投喂时间和频率等,以达到降低水产品污染物含量的目的。
The invention relates to the technical field of pollutant detection, and specifically discloses a method for detecting pollutants in aquatic products, comprising: step one: detecting aquatic products, evaluating the pollutant content of aquatic products, and generating a pollutant content evaluation signal; step two: based on the pollutant content abnormality signal, analyzing the relationship between feeding a target feed and aquatic product pollution, and generating a feeding influence signal, so as to facilitate the analysis of whether the feeding target feed will have an impact on the pollutant content of aquatic products; by collecting secretions of aquatic products for analysis, there is no need to destroy aquatic product samples, thereby ensuring the integrity and safety of aquatic products; after understanding the impact of feed feeding on the pollutant content of aquatic products, breeders can adjust feed formulas and feeding strategies according to actual conditions, select more environmentally friendly and safe feed, or change feeding time and frequency, etc., so as to achieve the purpose of reducing the pollutant content of aquatic products.
Description
技术领域Technical Field
本发明涉及污染物检测技术领域,具体涉及一种水产品中污染物的检测方法。The present invention relates to the technical field of pollutant detection, and in particular to a method for detecting pollutants in aquatic products.
背景技术Background Art
随着水产养殖业的快速发展,水产品安全问题日益受到关注,水产品中的污染物,如重金属,对消费者健康构成潜在威胁,传统的水产品污染物检测方法通常需要破坏水产品样本,不仅导致样本无法再次使用,还可能影响检测结果的准确性,因为破坏过程可能改变污染物的状态或浓度,且还需要专业人员来操作和维护专业的设备,增加了人力成本和技术门槛;因此需要一种简单快速的非破坏性的水产品检测方法。With the rapid development of aquaculture, the safety of aquatic products has received increasing attention. Pollutants in aquatic products, such as heavy metals, pose a potential threat to consumer health. Traditional methods for detecting pollutants in aquatic products usually require the destruction of aquatic product samples, which not only makes the samples unusable, but may also affect the accuracy of the test results because the destruction process may change the state or concentration of the pollutants. Professionals are also required to operate and maintain professional equipment, which increases labor costs and technical barriers. Therefore, a simple, fast, non-destructive method for detecting aquatic products is needed.
但是,传统的水产品污染物检测方法,并不能在检测污染物含量的同时了解饲料投喂对水产品污染物含量的影响,从而帮助养殖者可以根据实际情况调整饲料配方和投喂策略,选择更加环保、安全的饲料,或者改变投喂时间和频率等,以达到降低水产品污染物含量的目的。However, traditional methods for detecting pollutants in aquatic products cannot simultaneously detect the pollutant content and understand the impact of feed feeding on the pollutant content in aquatic products, thereby helping farmers to adjust feed formulas and feeding strategies according to actual conditions, choose more environmentally friendly and safe feeds, or change feeding time and frequency, etc., in order to achieve the goal of reducing the pollutant content in aquatic products.
发明内容Summary of the invention
本发明的目的在于提供一种水产品中污染物的检测方法,以解决上述背景中技术问题。The purpose of the present invention is to provide a method for detecting pollutants in aquatic products to solve the technical problems in the above background.
本发明的目的可以通过以下技术方案实现:The purpose of the present invention can be achieved through the following technical solutions:
一种水产品中污染物的检测方法,包括以下步骤:A method for detecting pollutants in aquatic products comprises the following steps:
步骤一:对水产品进行检测,并对水产品污染物含量进行评估,生成污染物含量评估信号;Step 1: Detect aquatic products and evaluate the pollutant content of aquatic products to generate a pollutant content evaluation signal;
其中,污染物含量评估信号包括:污染物含量正常信号和污染物含量异常信号;The pollutant content assessment signal includes: a normal pollutant content signal and an abnormal pollutant content signal;
步骤二:基于污染物含量异常信号,分析投喂目标饲料与水产品污染之间的关系,并生成投喂影响信号,从而便于分析投喂的目标饲料是否会对水产品的污染物含量产生影响;Step 2: Based on the abnormal signal of pollutant content, analyze the relationship between feeding target feed and aquatic product pollution, and generate feeding impact signal, so as to analyze whether the feeding target feed will affect the pollutant content of aquatic products;
其中,分析投喂目标饲料与水产品污染之间关系的具体过程为:Among them, the specific process of analyzing the relationship between feeding target feed and aquatic product pollution is as follows:
基于时间以及检测时间段内所有检测周期的污染物含量表征值,获取污染物含量波动曲线;Obtaining a pollutant content fluctuation curve based on time and pollutant content characterization values of all detection cycles within the detection period;
基于每次目标饲料投喂时间后,分析影响时间内污染物含量波动曲线的趋势,并生成曲线趋势信号;Based on each target feed feeding time, analyze the trend of the pollutant content fluctuation curve within the impact time and generate a curve trend signal;
其中,曲线趋势信号包括:曲线上升趋势信号和曲线下降趋势信号;The curve trend signal includes: a curve upward trend signal and a curve downward trend signal;
基于所有曲线趋势信号,分析投喂目标饲料与水产品污染之间的关系,并生成投喂影响信号。Based on all curve trend signals, the relationship between feeding target feed and aquatic product contamination is analyzed, and a feeding impact signal is generated.
作为本发明进一步的方案:所述对水产品进行检测,并对水产品污染物含量进行评估,生成污染物含量评估信号的具体过程为:As a further solution of the present invention: the specific process of testing aquatic products, evaluating the pollutant content of aquatic products, and generating pollutant content evaluation signals is as follows:
在水产品养殖过程中,收集目标检测周期内水产品的分泌物;During the aquaculture process, secretions of aquatic products are collected within the target detection period;
对水产品的分泌物进行分析,输出污染物含量表征值;Analyze the secretions of aquatic products and output the representative value of pollutant content;
基于污染物含量表征值,水产品污染物含量进行评估,生成污染物含量评估信号。Based on the pollutant content characterization value, the pollutant content of aquatic products is evaluated and a pollutant content evaluation signal is generated.
作为本发明进一步的方案:所述污染物含量表征值的获取过程为:As a further solution of the present invention: the process of obtaining the pollutant content characterization value is:
将分泌物进行区域性划分,获取分泌物子区域;Divide the secretion into regions to obtain secretion sub-regions;
分别对每个子区域的分泌物进行分析,检测其中污染物的种类和含量,并将不同种类的污染物含量进行加权求和,输出各子区域分泌物的污染物含量总和,将污染物含量总和与污染物含量总和阈值进行比值计算,输出污染物含量参数;Analyze the secretions of each sub-area respectively, detect the types and contents of pollutants therein, and perform weighted summation of the contents of different types of pollutants, output the sum of the pollutant contents of the secretions of each sub-area, calculate the ratio of the sum of the pollutant contents to the sum of the pollutant content threshold, and output the pollutant content parameter;
将各子区域分泌物的污染物含量参数进行差值计算,输出污染物含量参数偏差值;Perform difference calculation on the pollutant content parameters of the secretions in each sub-area and output the deviation value of the pollutant content parameters;
基于污染物含量参数偏差值,分析分泌物是否受到水质影响,并生成分泌物影响信号;Based on the deviation value of the pollutant content parameter, analyze whether the secretion is affected by the water quality and generate a secretion impact signal;
其中,分泌物影响信号包括:分泌物受到影响信号和分泌物未受影响信号;The secretion-affected signal includes: a secretion-affected signal and a secretion-unaffected signal;
基于分泌物未受影响信号,将分泌物所有子区域的污染物含量参数进行均值计算,输出污染物含量参数均值;Based on the unaffected signal of the secretion, the pollutant content parameters of all sub-areas of the secretion are averaged and the pollutant content parameter average is output;
基于所有未受到水质影响的分泌物,将所有分泌物的污染物含量参数均值进行求均值计算,输出污染物含量表征值,并将污染物含量表征值标记为WH。Based on all secretions that are not affected by water quality, the mean values of the pollutant content parameters of all secretions are averaged, and the pollutant content characterization value is output, and the pollutant content characterization value is marked as WH.
作为本发明进一步的方案:所述基于污染物含量参数偏差值,分析分泌物是否受到水质影响,并生成分泌物影响信号的具体过程为:As a further solution of the present invention: the specific process of analyzing whether the secretion is affected by the water quality based on the pollutant content parameter deviation value and generating the secretion impact signal is:
预设污染物含量参数偏差值阈值,将污染物含量参数偏差值与污染物含量参数偏差值阈值进行对比分析;Preset a pollutant content parameter deviation value threshold, and compare and analyze the pollutant content parameter deviation value with the pollutant content parameter deviation value threshold;
若污染物含量参数偏差值≤污染物含量参数偏差值阈值,则说明分泌物未受到水质的影响,生成分泌物未受影响信号;If the pollutant content parameter deviation value is less than or equal to the pollutant content parameter deviation value threshold, it means that the secretion is not affected by the water quality, and a secretion unaffected signal is generated;
若污染物含量参数偏差值>污染物含量参数偏差值阈值,则说明分泌物未受到水质的影响,生成分泌物受到影响信号。If the pollutant content parameter deviation value is greater than the pollutant content parameter deviation value threshold, it means that the secretion is not affected by the water quality, and a signal indicating that the secretion is affected is generated.
作为本发明进一步的方案:所述基于污染物含量表征值,水产品污染物含量进行评估,生成污染物含量评估信号的具体过程为:As a further solution of the present invention: the specific process of evaluating the pollutant content of aquatic products based on the pollutant content characterization value and generating the pollutant content evaluation signal is as follows:
预设污染物含量表征值阈值为WHY,将污染物含量表征值WH与污染物含量表征值阈值WHY进行对比分析;The pollutant content characterization value threshold is preset as WHY, and the pollutant content characterization value WH is compared and analyzed with the pollutant content characterization value threshold WHY;
若污染物含量表征值WH≤污染物含量表征值阈值WHY,则判定水产品污染物含量低,生成污染物含量正常信号;If the pollutant content characterization value WH ≤ the pollutant content characterization value threshold WHY, it is determined that the pollutant content of the aquatic product is low, and a pollutant content normal signal is generated;
若污染物含量表征值WH>污染物含量表征值阈值WHY,则判定水产品污染物含量高,生成污染物含量异常信号。If the pollutant content characterization value WH>the pollutant content characterization value threshold WHY, it is determined that the pollutant content of the aquatic product is high and a pollutant content abnormality signal is generated.
作为本发明进一步的方案:所述污染物含量波动曲线的获取过程为:As a further solution of the present invention: the process of obtaining the pollutant content fluctuation curve is:
基于以时间为X轴,污染物含量表征值为Y轴建立的二维坐标系,并将检测时间段内所有检测周期的污染物含量表征值依据时间进行代入,获取污染物含量表征值点位,通过平滑曲线将所有污染物含量表征值点位进行连接,即获取污染物含量波动曲线。Based on a two-dimensional coordinate system with time as the X-axis and the pollutant content characterization value as the Y-axis, the pollutant content characterization values of all detection cycles within the detection time period are substituted according to time to obtain the pollutant content characterization value points, and all the pollutant content characterization value points are connected by a smooth curve to obtain the pollutant content fluctuation curve.
作为本发明进一步的方案:所述影响时间∆T的获取过程为:As a further solution of the present invention: the acquisition process of the impact time ∆T is:
获取对应次数目标饲料投喂的投喂量参数WL以及投喂间隔参数WJ;Obtain the feeding amount parameter WL and feeding interval parameter WJ of the corresponding number of target feed feedings;
通过公式:,计算获得影响时间∆T,其中,∆t为预设时间间隔,a1、a2为预设比例因子,且均大于0。By formula: , calculate and obtain the impact time ∆T, where ∆t is the preset time interval, a 1 and a 2 are preset proportional factors, and both are greater than 0.
作为本发明进一步的方案:所述分析影响时间内污染物含量波动曲线的趋势,并生成曲线趋势信号的过程为:As a further solution of the present invention: the process of analyzing the trend of the pollutant content fluctuation curve within the impact time and generating the curve trend signal is:
对影响时间内污染物含量波动曲线的趋势进行分析;Analyze the trend of the pollutant content fluctuation curve within the impact time;
若影响时间内污染物含量波动曲线呈上升趋势,则生成曲线上升趋势信号;If the pollutant content fluctuation curve shows an upward trend during the impact time, a curve upward trend signal is generated;
若影响时间内污染物含量波动曲线呈下降趋势,则生成曲线下降趋势信号。If the pollutant content fluctuation curve shows a downward trend during the impact time, a curve downward trend signal is generated.
作为本发明进一步的方案:所述基于所有曲线趋势信号,分析投喂目标饲料与水产品污染之间的关系,并生成投喂影响信号的过程为:As a further solution of the present invention: the process of analyzing the relationship between feeding target feed and aquatic product pollution based on all curve trend signals and generating feeding impact signals is as follows:
基于所有曲线趋势信号,记录所有曲线上升趋势信号次数以及所有曲线趋势信号次数,将所有曲线上升趋势信号次数以及所有曲线趋势信号次数进行比值计算,输出影响系数;Based on all curve trend signals, record the number of all curve rising trend signals and the number of all curve trend signals, calculate the ratio of all curve rising trend signals and the number of all curve trend signals, and output the influence coefficient;
预设影响系数阈值,将影响系数与影响系数阈值进行对比分析;Preset the impact coefficient threshold, and compare and analyze the impact coefficient with the impact coefficient threshold;
若影响系数≤影响系数阈值,则表示投喂目标饲料与水产品污染之间没有关系,生成投喂无影响信号;If the impact coefficient is less than or equal to the impact coefficient threshold, it means that there is no relationship between the target feed and the pollution of aquatic products, and a signal of no impact of feeding is generated;
若影响系数>影响系数阈值,则表示投喂目标饲料与水产品污染之间没有关系,生成投喂有影响信号。If the impact coefficient is greater than the impact coefficient threshold, it means that there is no relationship between the target feed and the pollution of aquatic products, and a signal that feeding has an impact is generated.
本发明的有益效果:Beneficial effects of the present invention:
本发明通过定期对水产品分泌物进行检测,分析分泌物中污染物的含量,输出污染物含量表征值,再基于污染物含量表征值,水产品污染物含量进行评估,生成污染物含量评估信号,从而可以在水产品养殖过程中,在不破坏水产品的前提下,对水产品污染物进行检测,生成污染物含量评估信号,通过收集水产品的分泌物进行分析,无需破坏水产品样本,保证了水产品的完整性和安全性,同时便于养殖人员了解水产品的污染情况,为制定针对性的处理措施提供科学依据;本发明通过了解饲料投喂对水产品污染物含量的影响后,养殖者可以根据实际情况调整饲料配方和投喂策略,选择更加环保、安全的饲料,或者改变投喂时间和频率等,以达到降低水产品污染物含量的目的。附图说明The present invention periodically detects secretions of aquatic products, analyzes the content of pollutants in the secretions, outputs a pollutant content characterization value, and then evaluates the pollutant content of aquatic products based on the pollutant content characterization value to generate a pollutant content evaluation signal. Therefore, during the aquaculture process, pollutants in aquatic products can be detected and a pollutant content evaluation signal can be generated without destroying the aquatic products. By collecting secretions of aquatic products for analysis, there is no need to destroy aquatic product samples, thus ensuring the integrity and safety of aquatic products. At the same time, it is convenient for breeders to understand the pollution status of aquatic products and provide a scientific basis for formulating targeted treatment measures. After understanding the impact of feed feeding on the pollutant content of aquatic products, the present invention allows breeders to adjust feed formulas and feeding strategies according to actual conditions, select more environmentally friendly and safe feeds, or change feeding time and frequency, etc., to achieve the purpose of reducing the pollutant content of aquatic products. Description of the drawings
下面结合附图对本发明作进一步的说明。The present invention will be further described below in conjunction with the accompanying drawings.
图1是本发明方法流程图;Fig. 1 is a flow chart of the method of the present invention;
图2是本发明中对水产品污染物含量进行评估的方法流程图;FIG2 is a flow chart of a method for evaluating the content of pollutants in aquatic products according to the present invention;
图3是本发明中分析投喂目标饲料与水产品污染之间关系的方法流程图;3 is a flow chart of a method for analyzing the relationship between feeding target feed and aquatic product pollution in the present invention;
图4是本发明系统示意图。FIG. 4 is a schematic diagram of the system of the present invention.
具体实施方式DETAILED DESCRIPTION
下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本发明一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其它实施例,都属于本发明保护的范围。The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
实施例一:Embodiment 1:
请参阅图1、图2所示,本发明实施例所述的一种水产品中污染物的检测方法,包括以下步骤:Referring to FIG. 1 and FIG. 2 , a method for detecting pollutants in aquatic products according to an embodiment of the present invention comprises the following steps:
步骤一:对水产品进行检测,并对水产品污染物含量进行评估,生成污染物含量评估信号;Step 1: Detect aquatic products and evaluate the pollutant content of aquatic products to generate a pollutant content evaluation signal;
其中,污染物含量评估信号包括:污染物含量正常信号和污染物含量异常信号;The pollutant content assessment signal includes: a normal pollutant content signal and an abnormal pollutant content signal;
污染物包括:重金属;Pollutants include: heavy metals;
需要说明的是:重金属包括:铅、汞、镉、铬、砷;重金属往往来自饲料添加剂、工业废水或自然环境中的地质活动,重金属对水产品具有直接的毒性作用,影响水产品的生长、繁殖和生存能力,且重金属在生物体内具有累积性,重金属会通过食物链传递到更高级别的生物体内,导致高级别生物体内重金属的积累,从而对其造成更大的危害;It should be noted that heavy metals include lead, mercury, cadmium, chromium and arsenic. Heavy metals often come from feed additives, industrial wastewater or geological activities in the natural environment. Heavy metals have direct toxic effects on aquatic products, affecting their growth, reproduction and survival. Heavy metals are cumulative in organisms and can be transferred to higher-level organisms through the food chain, leading to the accumulation of heavy metals in higher-level organisms, causing greater harm to them.
在一些实施方案中,在水产品养殖过程中,收集目标检测周期内水产品的分泌物;In some embodiments, during aquaculture, secretions of aquatic products are collected within a target detection period;
其中,目标检测周期包括:一天;分泌物包括:尿液、黏液;Among them, the target detection period includes: one day; secretions include: urine, mucus;
对水产品的分泌物进行分析,输出污染物含量表征值;将污染物含量表征值WH与污染物含量表征值阈值WHY进行对比分析;Analyze the secretions of aquatic products and output the pollutant content characterization value; compare and analyze the pollutant content characterization value WH with the pollutant content characterization value threshold WHY;
若污染物含量表征值WH≤污染物含量表征值阈值WHY,则判定水产品污染物含量低,生成污染物含量正常信号;If the pollutant content characterization value WH ≤ the pollutant content characterization value threshold WHY, it is determined that the pollutant content of the aquatic product is low, and a pollutant content normal signal is generated;
若污染物含量表征值WH>污染物含量表征值阈值WHY,则判定水产品污染物含量高,生成污染物含量异常信号;If the pollutant content characterization value WH>the pollutant content characterization value threshold WHY, it is determined that the pollutant content of the aquatic product is high, and a pollutant content abnormality signal is generated;
示例性的,污染物含量表征值的获取过程为:Exemplarily, the process of obtaining the pollutant content characterization value is as follows:
将分泌物进行区域性划分,获取分泌物子区域;Divide the secretion into regions to obtain secretion sub-regions;
其中,区域划分的方法为:将分泌物从中心到外表面划分为若干个区域,且每个区域的体积一致;The method of area division is: the secretion is divided into several areas from the center to the outer surface, and the volume of each area is consistent;
利用光谱测试法,分别对每个子区域的分泌物进行分析,检测其中污染物的种类和含量,并将不同种类的污染物含量进行加权求和,输出各子区域分泌物的污染物含量总和,将污染物含量总和与污染物含量总和阈值进行比值计算,输出污染物含量参数;Using the spectral testing method, the secretions of each sub-area are analyzed respectively to detect the types and contents of pollutants therein, and the contents of different types of pollutants are weighted and summed to output the total pollutant content of the secretions of each sub-area, and the total pollutant content is calculated by ratio with the total pollutant content threshold to output the pollutant content parameter;
其中,包括光谱测试法:荧光光谱法;Among them, the spectral test methods include: fluorescence spectroscopy;
需要说明的是:加权求和是为了综合考虑不同污染物对整体污染水平的影响,因为不同的污染物会具有不同的毒性和环境风险;加权的依据包括:污染物的毒性:不同污染物对人体健康或环境的潜在危害程度不同,毒性更高的污染物在加权时则赋予更大的权重;污染物的生物累积性:一些污染物容易在生物体内累积,并通过食物链放大,对人类和生态系统造成更大影响,所以污染物在加权时还需考虑其生物累积性;It should be noted that the weighted summation is to comprehensively consider the impact of different pollutants on the overall pollution level, because different pollutants have different toxicity and environmental risks; the basis for weighting includes: Toxicity of pollutants: Different pollutants have different potential harm to human health or the environment, and pollutants with higher toxicity are given greater weights when weighting; Bioaccumulation of pollutants: Some pollutants tend to accumulate in organisms and amplify through the food chain, causing greater impact on humans and ecosystems, so the bioaccumulation of pollutants must also be considered when weighting;
将各子区域分泌物的污染物含量参数进行差值计算,输出污染物含量参数偏差值;Perform difference calculation on the pollutant content parameters of the secretions in each sub-area and output the deviation value of the pollutant content parameters;
基于污染物含量参数偏差值,分析分泌物是否受到水质影响,并生成分泌物影响信号;Based on the deviation value of the pollutant content parameter, analyze whether the secretion is affected by the water quality and generate a secretion impact signal;
其中,分泌物影响信号包括:分泌物受到影响信号和分泌物未受影响信号;The secretion-affected signal includes: a secretion-affected signal and a secretion-unaffected signal;
预设污染物含量参数偏差值阈值,将污染物含量参数偏差值与污染物含量参数偏差值阈值进行对比分析;Preset a pollutant content parameter deviation value threshold, and compare and analyze the pollutant content parameter deviation value with the pollutant content parameter deviation value threshold;
若污染物含量参数偏差值≤污染物含量参数偏差值阈值,则说明分泌物未受到水质的影响,生成分泌物未受影响信号;If the pollutant content parameter deviation value is less than or equal to the pollutant content parameter deviation value threshold, it means that the secretion is not affected by the water quality, and a secretion unaffected signal is generated;
若污染物含量参数偏差值>污染物含量参数偏差值阈值,则说明分泌物未受到水质的影响,生成分泌物受到影响信号;If the pollutant content parameter deviation value is greater than the pollutant content parameter deviation value threshold, it means that the secretion is not affected by the water quality, and a signal that the secretion is affected is generated;
需要说明的是:当水产品处于受污染的水质环境中时,水产品会通过皮肤、鳃或其他途径吸收或吸附水中的污染物,污染物可能会附着在分泌物的表面,也可能水质稀释分泌物表面的污染物含量,导致在检测时分泌物表面污染物的含量与分泌物内部的污染物含量不同;It should be noted that when aquatic products are in a polluted water environment, they will absorb or adsorb pollutants in the water through their skin, gills or other pathways. The pollutants may adhere to the surface of the secretions, or the water may dilute the pollutant content on the surface of the secretions, resulting in the content of pollutants on the surface of the secretions being different from that inside the secretions during testing.
基于分泌物未受影响信号,将分泌物所有子区域的污染物含量参数进行均值计算,输出污染物含量参数均值;Based on the unaffected signal of the secretion, the pollutant content parameters of all sub-areas of the secretion are averaged and the pollutant content parameter average is output;
基于所有未受到水质影响的分泌物,将所有分泌物的污染物含量参数均值进行求均值计算,输出污染物含量表征值,并将污染物含量表征值标记为WH;Based on all secretions that are not affected by water quality, the mean values of the pollutant content parameters of all secretions are calculated, and the pollutant content representation value is output, and the pollutant content representation value is marked as WH;
本发明实施例的构思为:随着水产养殖业的快速发展,水产品安全问题日益受到关注,水产品中的污染物,如重金属,对消费者健康构成潜在威胁,传统的水产品污染物检测方法通常需要破坏水产品样本,不仅导致样本无法再次使用,还可能影响检测结果的准确性,因为破坏过程可能改变污染物的状态或浓度,且还需要专业人员来操作和维护专业的设备,增加了人力成本和技术门槛;因此需要一种简单快速的非破坏性的水产品检测方法,通过定期对水产品分泌物进行检测,分析分泌物中污染物的含量,输出污染物含量表征值,再基于污染物含量表征值,水产品污染物含量进行评估,生成污染物含量评估信号,从而可以在水产品养殖过程中,在不破坏水产品的前提下,对水产品污染物进行检测,生成污染物含量评估信号,通过收集水产品的分泌物进行分析,无需破坏水产品样本,保证了水产品的完整性和安全性,同时便于养殖人员了解水产品的污染情况,为制定针对性的处理措施提供科学依据。The concept of the embodiment of the present invention is as follows: With the rapid development of aquaculture, the safety of aquatic products has received increasing attention. Pollutants in aquatic products, such as heavy metals, pose a potential threat to consumer health. Traditional aquatic product pollutant detection methods usually require the destruction of aquatic product samples, which not only makes the samples unusable, but also may affect the accuracy of the detection results, because the destruction process may change the state or concentration of the pollutants, and also requires professionals to operate and maintain professional equipment, which increases labor costs and technical barriers; therefore, a simple and fast non-destructive aquatic product detection method is needed, by regularly detecting aquatic product secretions, analyzing the content of pollutants in the secretions, outputting a pollutant content characterization value, and then based on the pollutant content characterization value, the pollutant content of the aquatic product is evaluated to generate a pollutant content evaluation signal, so that during the aquatic product breeding process, without destroying the aquatic product, the aquatic product pollutants can be detected and the pollutant content evaluation signal can be generated. By collecting the secretions of aquatic products for analysis, there is no need to destroy the aquatic product samples, which ensures the integrity and safety of the aquatic products, and at the same time facilitates the breeding personnel to understand the pollution of the aquatic products, providing a scientific basis for formulating targeted treatment measures.
实施例二:Embodiment 2:
在实施例一的基础上,请参阅图1、图3所示,本发明实施例所述的一种水产品中污染物的检测方法,还包括以下步骤:Based on the first embodiment, referring to FIG. 1 and FIG. 3 , a method for detecting pollutants in aquatic products according to an embodiment of the present invention further includes the following steps:
步骤二:基于污染物含量异常信号,分析投喂目标饲料与水产品污染之间的关系,并生成投喂影响信号,从而便于分析投喂的目标饲料是否会对水产品的污染物含量产生影响;Step 2: Based on the abnormal signal of pollutant content, analyze the relationship between feeding target feed and aquatic product pollution, and generate feeding impact signal, so as to analyze whether the feeding target feed will affect the pollutant content of aquatic products;
其中,投喂影响信号包括:投喂无影响信号和投喂有影响信号;Among them, the feeding impact signal includes: feeding no impact signal and feeding impact signal;
在一些实施方案中,基于时间以及检测时间段内所有检测周期的污染物含量表征值,获取污染物含量波动曲线;In some embodiments, a pollutant content fluctuation curve is obtained based on time and pollutant content characterization values of all detection cycles within the detection time period;
其中,检测时间段包括:30个检测周期;Among them, the detection period includes: 30 detection cycles;
获取在水产品养殖过程中,获取检测时间段内目标饲料投喂的时间;Obtain the time of feeding the target feed within the detection period during the aquaculture process;
基于每次目标饲料投喂时间后,分析影响时间内污染物含量波动曲线的趋势,并生成曲线趋势信号;Based on each target feed feeding time, analyze the trend of the pollutant content fluctuation curve within the impact time and generate a curve trend signal;
其中,曲线趋势信号包括:曲线上升趋势信号和曲线下降趋势信号;The curve trend signal includes: a curve upward trend signal and a curve downward trend signal;
基于所有曲线趋势信号,记录所有曲线上升趋势信号次数以及所有曲线趋势信号次数,将所有曲线上升趋势信号次数以及所有曲线趋势信号次数进行比值计算,输出影响系数;将影响系数与影响系数阈值进行对比分析;Based on all curve trend signals, record the number of all curve rising trend signals and the number of all curve trend signals, calculate the ratio of all curve rising trend signals and the number of all curve trend signals, and output the influence coefficient; compare and analyze the influence coefficient with the influence coefficient threshold;
若影响系数≤影响系数阈值,则表示投喂目标饲料与水产品污染之间没有关系,生成投喂无影响信号;If the impact coefficient is less than or equal to the impact coefficient threshold, it means that there is no relationship between the target feed and the pollution of aquatic products, and a signal of no impact of feeding is generated;
若影响系数>影响系数阈值,则表示投喂目标饲料与水产品污染之间没有关系,生成投喂有影响信号;If the impact coefficient is greater than the impact coefficient threshold, it means that there is no relationship between feeding the target feed and aquatic product pollution, and a signal that feeding has an impact is generated;
示例性的,污染物含量波动曲线的获取过程为:基于以时间为X轴,污染物含量表征值为Y轴建立的二维坐标系,并将检测时间段内所有检测周期的污染物含量表征值依据时间进行代入,获取污染物含量表征值点位,通过平滑曲线将所有污染物含量表征值点位进行连接,即获取污染物含量波动曲线;Exemplarily, the process of obtaining the pollutant content fluctuation curve is as follows: based on a two-dimensional coordinate system established with time as the X-axis and the pollutant content characterization value as the Y-axis, the pollutant content characterization values of all detection cycles within the detection time period are substituted according to time to obtain the pollutant content characterization value points, and all the pollutant content characterization value points are connected by a smooth curve, that is, the pollutant content fluctuation curve is obtained;
示例性的,影响时间∆T的获取过程为:获取对应次数目标饲料投喂的投喂量参数WL以及投喂间隔参数WJ;Exemplarily, the process of obtaining the impact time ∆T is as follows: obtaining a feeding amount parameter WL and a feeding interval parameter WJ corresponding to the number of target feed feedings;
其中,投喂量参数WL为:目标饲料投喂的投喂量与投喂量阈值之比;Among them, the feeding amount parameter WL is: the ratio of the feeding amount of the target feed to the feeding amount threshold;
投喂间隔参数WJ为:目标饲料该次投喂时间与目标饲料上一次投喂时间之间的时间间隔,将时间间隔与时间间隔阈值进行比值计算,即为投喂间隔参数;The feeding interval parameter WJ is: the time interval between the current feeding time of the target feed and the last feeding time of the target feed. The time interval is calculated by the ratio of the time interval threshold to obtain the feeding interval parameter.
通过公式:,计算获得影响时间∆T,其中,∆t为预设时间间隔,a1、a2为预设比例因子,且均大于0;By formula: , calculate and obtain the impact time ∆T, where ∆t is the preset time interval, a 1 and a 2 are preset proportional factors, and both are greater than 0;
需要解释说明的是:每一次目标饲料投喂后的影响时间均要根据对应次数目标饲料投喂进行计算;It should be explained that the impact time after each target feed is calculated based on the corresponding number of target feeds.
示例性的,分析影响时间内污染物含量波动曲线的趋势,并生成曲线趋势信号的过程为:对影响时间内污染物含量波动曲线的趋势进行分析;Exemplarily, the process of analyzing the trend of the pollutant content fluctuation curve within the impact time and generating the curve trend signal is: analyzing the trend of the pollutant content fluctuation curve within the impact time;
若影响时间内污染物含量波动曲线呈上升趋势,则生成曲线上升趋势信号;If the pollutant content fluctuation curve shows an upward trend during the impact time, a curve upward trend signal is generated;
若影响时间内污染物含量波动曲线呈下降趋势,则生成曲线下降趋势信号;If the pollutant content fluctuation curve shows a downward trend during the impact time, a curve downward trend signal is generated;
本发明实施例的构思为:影响系数反映的是:目标饲料投喂后影响时间内污染物含量表征值的变化情况,影响系数的数值越大则污染物含量表征值呈上升趋势的次数越多,通过了解饲料投喂对水产品污染物含量的影响后,养殖者可以根据实际情况调整饲料配方和投喂策略,选择更加环保、安全的饲料,或者改变投喂时间和频率等,以达到降低水产品污染物含量的目的。The concept of the embodiment of the present invention is that the influence coefficient reflects the change in the pollutant content characterization value within the influence time after the target feed is fed. The larger the value of the influence coefficient, the more times the pollutant content characterization value shows an upward trend. After understanding the impact of feed feeding on the pollutant content of aquatic products, the breeder can adjust the feed formula and feeding strategy according to the actual situation, choose a more environmentally friendly and safe feed, or change the feeding time and frequency, etc., to achieve the purpose of reducing the pollutant content of aquatic products.
实施例三:Embodiment three:
在实施例一和实施例二的基础上,请参阅图4所示,本发明实施例所述的一种水产品中污染物的检测系统,包括:Based on the first and second embodiments, please refer to FIG. 4 , a system for detecting pollutants in aquatic products according to an embodiment of the present invention includes:
污染物含量评估模块用于对水产品进行检测,并对水产品污染物含量进行评估,生成污染物含量评估信号;The pollutant content assessment module is used to detect aquatic products, assess the pollutant content of the aquatic products, and generate a pollutant content assessment signal;
饲料投喂影响分析模块用于基于污染物含量异常信号,分析投喂目标饲料与水产品污染之间的关系,并生成投喂影响信号,从而便于分析投喂的目标饲料是否会对水产品的污染物含量产生影响。The feed impact analysis module is used to analyze the relationship between feeding target feed and aquatic product pollution based on abnormal pollutant content signals, and generate feeding impact signals, so as to facilitate the analysis of whether the feeding target feed will affect the pollutant content of aquatic products.
上述阈值的大小的设定是为了便于比较,关于阈值的大小,取决于样本数据的多少及本领域技术人员对每一组样本数据设定基数数量;The above thresholds are set for the convenience of comparison. The thresholds depend on the amount of sample data and the number of bases set by technicians in this field for each set of sample data.
上述公式均是采集大量数据进行软件模拟得出且选取与真实值接近的一个公式,公式中的因子是由本领域技术人员根据实际情况进行设置;如:公式;由本领域技术人员采集多组投喂量参数以及投喂间隔参数的检测数据并对每一组检测数据设定对应的影响时间;将设定的影响时间和采集的检测数据代入公式,任意三个公式构成三元一次方程组,将计算得到的因子进行筛选并取均值,得到、的取值分别为3.47和2.23;The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula close to the actual value. The factors in the formula are set by technicians in this field according to actual conditions; for example: Formula ; A technician in this field collects multiple groups of test data of feeding amount parameters and feeding interval parameters and sets a corresponding impact time for each group of test data; substitutes the set impact time and the collected test data into the formula, any three formulas constitute a three-variable linear equation group, and the calculated factors are screened and averaged to obtain , The values of are 3.47 and 2.23 respectively;
因子的大小是为了将各个参数进行量化得到的一个具体的数值,便于后续比较,关于因子的大小,取决于检测数据的多少及本领域技术人员对每一组检测数据初步设定对应的影响时间;只要不影响参数与量化后数值的比例关系即可,如影响时间与投喂量参数的数值成正比。The size of the factor is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the factor depends on the amount of test data and the initial setting of the corresponding impact time for each set of test data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the impact time is proportional to the value of the feeding amount parameter.
以上对本发明的一个实施例进行了详细说明,但所述内容仅为本发明的较佳实施例,不能被认为用于限定本发明的实施范围。凡依本发明申请范围所作的均等变化与改进等,均应仍归属于本发明的专利涵盖范围之内。The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.
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舟甬附近海域沉积物与大黄鱼、鲈鱼组织中的重金属研究;秦鹤;中国优秀硕士学位论文全文数据库(电子期刊)工程科技Ⅰ辑;20180115;第B027-109页 * |
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