CN103229737A - Method for forecasting large-scale bacteriosis occurrence time of cage-cultured pseudosciaena crocea - Google Patents

Method for forecasting large-scale bacteriosis occurrence time of cage-cultured pseudosciaena crocea Download PDF

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CN103229737A
CN103229737A CN201310151245XA CN201310151245A CN103229737A CN 103229737 A CN103229737 A CN 103229737A CN 201310151245X A CN201310151245X A CN 201310151245XA CN 201310151245 A CN201310151245 A CN 201310151245A CN 103229737 A CN103229737 A CN 103229737A
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倪海儿
王国良
吴雄飞
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Ningbo University
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Abstract

本发明公开了网箱养殖大黄鱼细菌性疾病大规模发生时间的预报，以预报前几年细菌性疾病大规模发生时间为基数，根据发病规律，建立预测模型，然后根据预测模型，预测下期发病时间。形成的大黄鱼大规模细菌性疾病发生的预报技术，可解决大黄鱼大规模细菌性疾病发生的提前预报、提前预防问题。所需的数据资料少，而且操作简单，只需要有得到4次以上发病月份的记录，经简单计算便可预测下期的发病时间。本发明首次创建了养殖大黄鱼大规模细菌性疾病的预报技术，因为它是根据大黄鱼细菌性疾病的发病规律建立的预报方法，因此适用范围广，可用于池塘、网箱等各种养殖方式。The invention discloses the forecast of large-scale occurrence time of bacterial diseases in cage cultured large yellow croaker. Taking the forecast of the large-scale occurrence time of bacterial diseases in previous years as the base, a prediction model is established according to the law of onset, and then according to the prediction model, the next period of onset is predicted. time. The formed large-scale bacterial disease forecasting technology of large yellow croaker can solve the problem of early prediction and early prevention of large-scale bacterial disease of large yellow croaker. The required data are few, and the operation is simple. It only needs to have more than 4 records of the onset month, and the onset time of the next period can be predicted by simple calculation. The present invention creates the large-scale bacterial disease forecasting technology of large yellow croaker for the first time, because it is a forecast method established according to the pathogenesis of large yellow croaker bacterial disease, so it has a wide range of applications and can be used in various breeding methods such as ponds and net cages .

Description

网箱养殖大黄鱼细菌性疾病大规模发生时间的预报Forecast of large-scale occurrence time of bacterial diseases in cage cultured large yellow croaker

技术领域technical field

本发明涉及网箱养殖大黄鱼的疾病控制技术，具体涉及网箱养殖大黄鱼细菌性疾病大规模发生时间的预报。The invention relates to a disease control technology for large yellow croaker cultured in net cages, in particular to the prediction of large-scale occurrence time of bacterial diseases of large yellow croaker cultured in net cages.

背景技术Background technique

大黄鱼是重要的海水养殖品种，其疾病种类多、发病率高，其中细菌性疾病是最主要的疾病，细菌性疾病引起的死亡率己达到大黄鱼养殖期间总死亡率的40%以上，因此是大黄鱼养殖生产中危害最大的疾病之一。细菌性疾病发病速度快，范围广，常造成暴发性流行，据调查舟山市几乎每年都有一次大模范的细菌疾病发生，发病水体多在20%以上。细菌性疾病一旦暴发，就只能依靠各种抗菌药物治疗，但由于其发病范围广，传播速度快，因此发现疾病后的药物治疗往往收效甚微。为防止大黄鱼细菌性疾病的大规模发生，在养殖过程中也常采取不定时用药的方法，进行经常性的用药，这种用药的盲目性、随意性，不仅收不到防治效果，而且还造成病原菌耐药性增加、养殖环境恶化等生态环境问题以及水产品药物残留等食品安全问题。如能提前预知大黄鱼细菌性疾病的发生，就可适时、准确地采取预防措施，防止疾病的发生，避免盲目用药带来的不良后果，减少由疾病带来的经济损失。虽然我国已有专利与为200710068792.6的一种人工养殖大黄鱼的疾病发生的预警方法，它是根据透明度、水温和平均风力预测疾病发病的程度，由于大黄鱼疾病种类多，该技术无法确定将发生的疾病的种类，因此对采取针对性的预防措施难度较大。Large yellow croaker is an important marine cultured species. It has many types of diseases and a high incidence rate. Among them, bacterial diseases are the most important diseases. The mortality caused by bacterial diseases has reached more than 40% of the total mortality during large yellow croaker cultivation. Therefore, It is one of the most harmful diseases in the production of large yellow croaker. The incidence of bacterial diseases is fast and the scope is wide, often causing explosive epidemics. According to the survey, there is a large scale of bacterial diseases in Zhoushan City almost every year, and the incidence of water bodies is more than 20%. Once a bacterial disease breaks out, it can only be treated with various antibacterial drugs. However, due to its wide range of incidence and fast transmission speed, the drug treatment after the disease is discovered often has little effect. In order to prevent the large-scale occurrence of large-scale bacterial diseases of large yellow croaker, the method of irregular medication is often used in the breeding process, and regular medication is used. The blindness and randomness of this medication not only fail to achieve the control effect, but also It has caused ecological and environmental problems such as increased drug resistance of pathogenic bacteria, deterioration of the breeding environment, and food safety problems such as drug residues in aquatic products. If the occurrence of bacterial diseases of large yellow croaker can be predicted in advance, preventive measures can be taken timely and accurately to prevent the occurrence of diseases, avoid adverse consequences caused by blind medication, and reduce economic losses caused by diseases. Although our country already has a patent of 200710068792.6 on an early warning method for disease occurrence of artificially cultured large yellow croaker, it predicts the degree of disease incidence based on transparency, water temperature and average wind force. Therefore, it is more difficult to take targeted preventive measures.

发明内容Contents of the invention

本发明所要解决的技术问题是提供在网箱养殖大黄鱼，可提前预知细菌性疾病大规模发生时间的预报技术，达到发生前及时预防，避免细菌性疾病大规模发生。The technical problem to be solved by the present invention is to provide a forecasting technology that can predict the large-scale occurrence time of bacterial diseases in advance by cultivating large yellow croakers in cages, so as to prevent them in time before the occurrence and avoid the large-scale occurrence of bacterial diseases.

本发明解决上述技术问题所采用的技术方案为：网箱养殖大黄鱼细菌性疾病大规模发生时间的预报，其步骤如下：The technical solution adopted by the present invention to solve the above-mentioned technical problems is: the prediction of the time of large-scale occurrence of bacterial diseases of large yellow croaker in cage culture, and its steps are as follows:

a、对大黄鱼网箱养殖海区，连续调查n次大规模细菌性疾病发生的时间，n＞3，以调查起始年的第一个月为起始月，从起始月起算，记录各次大规模细菌性疾病发生的月数，依次记为x1,x2,…,xn；a. For large yellow croaker cage culture sea areas, continuously investigate the occurrence time of n large-scale bacterial diseases, n > 3, take the first month of the survey starting year as the starting month, and record each The number of months when the sub-large-scale bacterial disease occurred, recorded as x 1 , x 2 ,…, x n in turn;

b、以x1,x2,…,xn为基数，在y1=x1下，后一数值与前面数依次累加得到y1,y2,...,yn；b. Taking x 1 , x 2 ,..., x n as the base, under y 1 = x 1 , the latter value and the previous number are accumulated in sequence to obtain y 1 , y 2 ,..., y n ;

c、以y1,y2,…,yn为基数，将前后相邻两数相加后除以2，得到z2,z3…,zn；c. Taking y 1 , y 2 ,..., y n as the base, add the two adjacent numbers before and after and divide by 2 to get z 2 , z 3 ..., z n ;

d、将x2,...,xn的平均值记为

Figure BDA00003110797200021
z2,z3...,zn的平均值
Figure BDA00003110797200022
c=x2z2+x3z3+…+xnzn，以
Figure BDA00003110797200024
Figure BDA00003110797200025
求出a和b；a和b反应发病时间的变化态势和发病时间之间的相互关系；d. Record the average value of x 2 ,...,x n as
Figure BDA00003110797200021
z 2 , z 3 ..., z n mean
Figure BDA00003110797200022
c=x 2 z 2 +x 3 z 3 +…+x n z n , with
Figure BDA00003110797200024
Figure BDA00003110797200025
Obtain a and b; a and b reflect the changing trend of onset time and the relationship between onset time;

e、以下式得到第n次以后各次细菌性疾病大规模发生时间的预测：

Figure BDA00003110797200026
，k=0,1,2,…，得到从起始月起算，第(n+k+1)次大规模细菌性疾病发生的月数。e. The following formula obtains the prediction of the large-scale occurrence time of each bacterial disease after the nth time:
Figure BDA00003110797200026
, k=0,1,2,…, get the number of months when the (n+k+1)th large-scale bacterial disease occurred from the initial month.

与现有技术相比，本发明的优点在于网箱养殖大黄鱼细菌性疾病大规模发生时间的预报，以预报前几年细菌性疾病大规模发生时间为基数，根据发病规律，建立预测模型，然后根据预测模型，预测下期发病时间。形成的大黄鱼大规模细菌性疾病发生的预报技术，可解决大黄鱼大规模细菌性疾病发生的提前预报、提前预防问题。所需的数据资料少，而且操作简单，只需要有得到4次以上发病月份的记录，经简单计算便可预测下期的发病时间。本发明首次创建了养殖大黄鱼大规模细菌性疾病的预报技术，因为它是根据大黄鱼细菌性疾病的发病规律建立的预报方法，因此适用范围广，可用于池塘、网箱等各种养殖方式。Compared with the prior art, the present invention has the advantage of forecasting the large-scale occurrence time of bacterial diseases in large yellow croaker cultured in cages. Based on the prediction of the large-scale occurrence time of bacterial diseases in the previous few years, a prediction model is established according to the law of onset. Then, according to the prediction model, the onset time of the next period is predicted. The formed large-scale bacterial disease forecasting technology of large yellow croaker can solve the problem of early prediction and early prevention of large-scale bacterial disease of large yellow croaker. The required data are few, and the operation is simple. It only needs to have more than 4 records of the onset month, and the onset time of the next period can be predicted by simple calculation. The present invention creates the large-scale bacterial disease forecasting technology of large yellow croaker for the first time, because it is a forecast method established according to the pathogenesis of large yellow croaker bacterial disease, so it has a wide range of applications and can be used in various breeding methods such as ponds and net cages .

具体实施方式Detailed ways

以下结合实施例对本发明作进一步详细描述。Below in conjunction with embodiment the present invention is described in further detail.

实施例Example

调查舟山市一个大黄鱼网箱养殖海区，在2001-2006年之间，发现有6次大规模细菌性疾病发生，6次发病时间依次为2001年9月，2002年9月，2003年8月，2004年10，2005年7月，2006年8，根据本发明的方法，建立发病时间的预测技术如下：Investigating a large yellow croaker cage culture sea area in Zhoushan City, between 2001 and 2006, it was found that there were 6 large-scale bacterial diseases, and the 6 outbreaks occurred in September 2001, September 2002, and August 2003. , October 2004, July 2005, August 2006, according to the method of the present invention, the prediction technology for establishing the onset time is as follows:

1、根据调查结果，以2001年1月为起始月，得到各次疾病发生的时间x1,x2,…,x6为9,21,32,46,55,68；1. According to the survey results, taking January 2001 as the starting month, the times x 1 , x 2 ,..., x 6 of each disease occurrence are 9, 21, 32, 46, 55, 68;

2、以y1=x1=9，在9,21,32,46,55,68基数下，后一数与其前面的数值依次累加得到y1,y2,…,y6为9,30,62,108,163,231；2. With y 1 =x 1 =9, under the base numbers of 9, 21, 32, 46, 55, 68, the latter number and the previous value are accumulated in sequence to obtain y 1 , y 2 ,..., y 6 are 9, 30 ,62,108,163,231;

3、将以上y1,y2,…,y6计算相邻两个元素的平均值，得到z2,z3…,z6为19.5,46,85,135.5,197;3. Calculate the average value of the above y 1 , y 2 ,..., y 6 adjacent two elements, and get z 2 , z 3 ..., z 6 as 19.5, 46, 85, 135.5, 197;

4、进而可得x2,…,x6的平均值

Figure BDA00003110797200031
z2,z3,…,z6的平均值
Figure BDA00003110797200032
计算得到zp=66890.5，计算c=x2z2+x3z3+…+x6z6得到c=26640，从
Figure BDA00003110797200034
计算得到a=-0.2568，计算
Figure BDA00003110797200035
得到b=19.5977。4. Then the average value of x 2 ,…,x 6 can be obtained
Figure BDA00003110797200031
Average value of z 2 ,z 3 ,…,z 6
Figure BDA00003110797200032
calculate to get z p = 66890.5, calculate c = x 2 z 2 + x 3 z 3 + ... + x 6 z 6 to get c = 26640, from
Figure BDA00003110797200034
Calculate a=-0.2568, calculate
Figure BDA00003110797200035
Get b=19.5977.

5、根据，可预测该大黄鱼网箱养殖海区第7次（K=0）细菌性疾病大规模发生时间为2001年1月起的第90.2个月，即2006年8月发病后再次发病的时间是2008年6月末7月初，根据这个预测，2007年不会发生大规模的细菌性疾病，结果证实2007年确实未发生，而在2008年7月初确实发生了大规模的细菌性疾病。其后预测下一次即2001年起第8次细菌性疾病大规模发生时间为2001年1月起的第116.61个月，即为2010年8月底9月初，因此从2010年8月开始，对试验区网箱养殖的大黄鱼，加强了监测，并进行了药物预防和养殖密度的调整，结果抑制了该区细菌性疾病大规模发生。而未采取预防措施的区域在2010年9月初发生了疾病。5. According to , it can be predicted that the 7th (K=0) large-scale occurrence of bacterial disease in the sea area of large yellow croaker cage culture will be the 90.2th month from January 2001, that is, the time of recurrence after the onset in August 2006 is 2008 At the end of June and early July of 2007, according to this prediction, no large-scale bacterial disease would occur in 2007. The results confirmed that there was indeed no large-scale bacterial disease in 2007, and that a large-scale bacterial disease did occur in early July 2008. Then it is predicted that the next time, that is, the 8th large-scale occurrence of bacterial diseases from 2001 will be the 116.61th month from January 2001, that is, the end of August and the beginning of September 2010. Therefore, starting from August 2010, the test The large yellow croaker raised in cages in the area has been monitored, and drug prevention and adjustment of breeding density have been carried out. As a result, the large-scale occurrence of bacterial diseases in this area has been suppressed. Disease occurred in early September 2010 in areas where preventive measures were not taken.

若K=0预测成功后，K=1预测时，可以将K=0时的发病月数作为调查得到各次疾病发生的时间使用，对K=1预测更准确，依次类推。If K=0 prediction is successful, when K=1 prediction, the number of months of onset when K=0 can be used as the time of occurrence of each disease obtained from the investigation, the prediction of K=1 is more accurate, and so on.

本发明是对舟山群岛、宁波象山港、三门湾、宁德等网箱养殖大黄鱼多个海区，系统调查连续3次以上大规模细菌性疾病发生时间，在K=0，K=1下验证下，反复研究，得出y1,y2,…,y6是x1,x2,…,x6为基数下依次累加为准，z2,z3…,z6是在y1,y2,…,y6为基数下的相邻两个元素的平均值为准，然后创造了公式（发病时间的变化态势），

Figure BDA00003110797200038
（发病时间之间的相互关系），和预测发病月份的公式：
Figure BDA00003110797200039
，其中X平均值、Z平均值、ZP和C的使用及得出方式也是创造性的，e为常数。具体验证与实施例基本相似，就是各次发病的X基础数据有所区别，K=0，或者K=1下验证的月份有所区别，但都在舟山群岛、宁波象山港、三门湾、宁德等网箱养殖大黄鱼多个海区得到证实，在此不一一列举。The present invention systematically investigates the occurrence time of large-scale bacterial diseases for more than 3 consecutive times in several sea areas such as Zhoushan Islands, Ningbo Xiangshan Port, Sanmen Bay, Ningde and other cage cultured large yellow croakers, and verifies under K=0, K=1 After repeated research, it is obtained that y 1 , y 2 ,...,y 6 are based on x 1 , x 2 ,...,x 6 and are accumulated sequentially, and z 2 , z 3 ..., z 6 are based on y 1 , y 2 ,..., y 6 are the average value of the two adjacent elements under the base, and then create the formula (the changing trend of onset time),
Figure BDA00003110797200038
(the relationship between the onset time), and the formula for predicting the onset month:
Figure BDA00003110797200039
, wherein the use and derivation of X mean value, Z mean value, Z P and C are also creative, and e is a constant. The specific verification is basically similar to the example, that is, the X basic data of each disease is different, and the month of verification under K=0 or K=1 is different, but they are all in Zhoushan Islands, Ningbo Xiangshan Port, Sanmen Bay, Cage culture of large yellow croaker in Ningde and other sea areas has been confirmed, so I will not list them here.

Claims (1)

1.网箱养殖大黄鱼细菌性疾病大规模发生时间的预报，其特征在于步骤如下：1. The prediction of the large-scale occurrence time of the large yellow croaker bacterial disease in cage culture is characterized in that the steps are as follows: a、对大黄鱼网箱养殖海区，连续调查n次大规模细菌性疾病发生的时间，n＞3，以调查起始年的第一个月为起始月，从起始月起算，记录各次大规模细菌性疾病发生的月数，依次记为x1,x2,…,xn；a. For large yellow croaker cage culture sea areas, continuously investigate the occurrence time of n large-scale bacterial diseases, n > 3, take the first month of the survey starting year as the starting month, and record each The number of months when the sub-large-scale bacterial disease occurred, recorded as x 1 , x 2 ,…, x n in turn; b、以x1,x2,…,xn为基数，在y1=x1下，后一数值与前面数依次累加得到y1,y2,…,yn；b. Taking x 1 , x 2 ,...,x n as the base, under y 1 =x 1 , the latter value and the previous number are accumulated in turn to obtain y 1 , y 2 ,...,y n ; c、以y1,y2,…,yn为基数，将前后相邻两数相加后除以2，得到z2,z3…,zn；c. Taking y 1 , y 2 ,..., y n as the base, add the two adjacent numbers before and after and divide by 2 to get z 2 , z 3 ..., z n ; d、将x2,…,xn的平均值记为
Figure FDA00003110797100011
z2,z3…,zn的平均值
Figure FDA00003110797100012
Figure FDA00003110797100013
c=x2z2+x3z3+…+xnzn，以
Figure FDA00003110797100014
Figure FDA00003110797100015
求出a和b；a和b反应发病时间的变化态势和发病时间之间的相互关系；d. Record the average value of x 2 ,…,x n as
Figure FDA00003110797100011
The average value of z 2 ,z 3 ...,z n
Figure FDA00003110797100012
Figure FDA00003110797100013
c=x 2 z 2 +x 3 z 3 +…+x n z n , with
Figure FDA00003110797100014
Figure FDA00003110797100015
Obtain a and b; a and b reflect the changing trend of onset time and the relationship between onset time; e、以下式得到第n次以后各次细菌性疾病大规模发生时间的预测：
Figure FDA00003110797100016
，k=0,1,2,…，得到从起始月起算，第(n+k+1)次大规模细菌性疾病发生的月数。e. The following formula obtains the prediction of the large-scale occurrence time of each bacterial disease after the nth time:
Figure FDA00003110797100016
, k=0,1,2,…, get the number of months when the (n+k+1)th large-scale bacterial disease occurred from the initial month.
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