METHOD AND QUALITY SYSTEM FOR DETERMINING A QUALITY PARAMETER OF AN AGRICULTURAL GROUP

Abstract

A quality system comprising a computer system and an analyzing system adapted for analyzing samples of particles collected from air from an agricultural group location. The analyzing system is configured for receiving a plurality of samples of particles collected at the agricultural group location, for performing at least one quantitative, biological element determination of each of the received samples; and transmitting sub-sets of data to the computer system, which correlates the data sub-sets with reference data. The reference data represents reference quantity of the biological element as a function of time correlated to the quality parameter and comprises at least one threshold quality parameter of the biological element as a function of time. The determination of the quality parameter comprises determining quantity of the biological element as a function of time and wherein the computer further is configured for determine the quality parameter relative to the at least one threshold quality parameter.

Claims

1-102. (canceled)

103. A method of determining a quality parameter of an agricultural group located at an agricultural group location, the method comprising providing a plurality of samples, each sample comprises particles or fragment(s) of particles collected from air from said agricultural group location at consecutive, selected time slots wherein each sample being correlated with a time attribute representing a time of collection; performing at least one quantitative, biological element determination of each of said samples to obtain data sub-sets comprising for each sample the result of said at least one determination and said time attribute for said sample. correlating one or more of said data sub-sets with reference data comprising at least one set of reference data; and determining said quality parameter of the agricultural group, wherein said set of reference data represents reference quantity of said biological element as a function of time correlated to said quality parameter comprising at least one threshold quality parameter of said at least one biological element as a function of time and wherein the determination of said quality parameter comprises determining quantity of said at least one biological element as a function of time and wherein the method further comprises determining said quality parameter relative to said at least one threshold quality parameter.

104. The quality system of claim 103, wherein the set of reference data comprises event data representing the quality parameter of the agricultural group and the agricultural group location as a function of time relative to an initial event and wherein the agricultural group is selected from a flock of animals, a feed lot and/or an animal bedding lot.

105. The quality system of claim 103, wherein said threshold quality parameter comprises at least one of a threshold quantity of said at least one biological element; a threshold drift of quantity of said at least one biological element as a function of time and/or a threshold change of quantity of said biological element as a function of time.

106. The method of claim 103, wherein the quality parameter is a quantity parameter or a derived quantity parameter selected from a parameter of quantity of said biological element, a parameter of quantity of said biological element at a selected time from the initial event, a parameter of quantity of said biological element relative to a threshold, a parameter of quantity of said biological element relative to a quantity of one or more other biological elements.

107. The method of claim 103, wherein the method comprises collecting said particles, wherein said particles being collected according to predetermined collecting instructions, said predetermined collection instructions comprises instructions of time slots for collecting particles, instructions of collecting time, instructions of location and/or movement of collector relative to elements of the agricultural group.

108. The method of claim 103, wherein the method comprises collecting said particles using a collector selected from an electrostatic collector and/or a filter collector.

109. The method of claim 103, wherein said set(s) of reference data represents at least one threshold change of quantity of said biological element as a function of time from an initial event correlated to a selected level of said quality parameter, wherein said agricultural group is a flock of animals and said agricultural group location is an animal location, wherein said initial event is selected from hatching, birth, vaccinating, medicating, detection of disease related pathogens, movement of animals, change of light setting, feed change, and/or outbreaks in neighboring herds or wherein said agricultural group is a feed lot and said agricultural group location is a feed lot location or said agricultural group is an animal bedding lot and said agricultural group location is an animal bedding lot location and wherein said initial event is selected from a change of temperature, change of location, change in humidity, change of season, mixing with another feed lot and/or breach of a biosecurity protocol.

110. The method of claim 103, wherein the agricultural group is a flock of animals, and the agricultural group location is an animal location and wherein the quality parameter is a quality parameter of the flock of animals selected from a biological parameter, a health parameter, a growth parameter, a meat quality parameter or a production parameter.

111. The method of claim 103, wherein the agricultural group is a feed lot and said agricultural group location is a feed lot location, wherein the quality parameter is selected from a durability parameter, crispness parameter, a palatability parameter, a chemical parameter and/or biological parameter.

112. A quality system for determining a quality parameter of agricultural group suitably for use in the method of claim 103, the quality system comprising a computer system in data communication with an analyzing system adapted for analyzing samples of particles collected from air from an agricultural group location comprising the agricultural group, wherein the analyzing system is configured for receiving a plurality of samples, each sample comprises particles or fragment(s) of particles collected from air from said agricultural group location at plurality of consecutive selected time slots and each sample being correlated with a time attribute representing a time of collection; for performing at least one quantitative, biological element determination of each of said received samples; and for transmitting sub-sets of data, each comprising data representing said at least one quantitative, biological element determination of a sample and the time attribute of said sample to said computer system; wherein the computer system is configured for receiving said sub-sets of data; for correlating said received sub-sets of data with at least one set of reference data; and for determining said quality parameter of the agricultural group, wherein said set of reference data represents reference quantity of said biological element as a function of time correlated to said quality parameter comprising at least one threshold quality parameter of said at least one biological element as a function of time and wherein the determination of said quality parameter comprises determining quantity of said at least one biological element as a function of time and wherein the computer further is configured for determine said quality parameter relative to said at least one threshold quality parameter.

113. The quality system of claim 112, wherein the set of reference data comprises event data representing the quality parameter of the agricultural group and the agricultural group location as a function of time relative to an initial event.

114. The quality system of claim 109, wherein the computer system and/or a data cloud storage in data communication with said computer system stores said at least one set of reference data, said sets of reference data each comprises reference data representing quantity of said biological element as a function of time correlated to said quality parameter, wherein said at least one set of reference data comprises reference data representing at least one quality parameter associated to at least one type of agricultural group and/or type of agricultural group location and suitable for being applied for reference data for determining said at least one quality parameter for said respective type of agricultural group and/or type of agricultural group location.

115. The quality system of claim 112, wherein the quality parameter is selected from a parameter of quantity of said biological element, a parameter of quantity of said biological element at a selected time from an initial event, a parameter of quantity of said biological element relative to a threshold, a parameter of quantity of said biological element relative to a quantity of one or more other biological elements and/a derived parameter of one or more of these.

116. The quality system of claim 112, wherein the computer system and/or the data cloud storage stores data representing instructions for collecting particles from air, wherein the data representing instructions for collecting particles from air comprises a database of collecting instructions correlated to at least one type of agricultural group and/or type of agricultural group location, wherein the collecting instructions comprises instructions of time slots for collecting particles, instructions of collecting time, instructions of location and/or movement of collector relative to animals of the flock of animals or relative to the feed of the feed lot.

117. The quality system of claim 112, wherein the system comprises a collector adapted for collecting at least partly airborne particles, wherein the collector is an electrostatic collector or a filter collector and wherein at least a part of the analyzing system is integrated with the collector to provide that the analyzer configured for at least partly performing the at least one quantitative, biological element determination of each of said received samples, wherein the analyzer is configured for performing a PCR amplification, sequencing, mass spectroscopy, high pressure liquid chromatography, incubation, microbiological examination and/or optical identification.

118. The quality system of claim 112, wherein the computer system is configured for receiving said consecutively sub-sets of said data in real time as they are generated by the analyzing system, wherein the computer system is configured for correlating said received consecutively sub-sets of said data with said reference data in real time as they are received by the computer system and for each of said correlations with reference data, performing said determination of said quality parameter of agricultural group.

119. The quality system of claim 112, wherein said threshold is a selected level of said quality parameter, wherein said selected level of said quality parameter is a level where the quality parameter indicates a raised risk, such as a risk of low production, low growth, of undesired infection, of increase in mortality rate, of decay of feed lot, a zoonotic risks and/or any other raise in risk of decrease in quality.

120. The quality system of claim 112, wherein said computer system based on the determined quality parameter is configured for determining a diagnosis, an indication of a diagnosis, a treatment and/or an indication of a treatment for improving the state of the agricultural group, when said determined quality parameter is outside or inside a threshold range and/or where the quality parameter is exceeding a threshold.

121. The quality system of claim 112, wherein said at least one set of reference data comprises said threshold in the form of at least one threshold change of quantity of said biological element as a function of time from the initial event and wherein said agricultural group is a flock of animals and said agricultural group location is an animal location, said initial event is selected from hatching, birth, vaccinating, medicating, detection of disease related pathogens, movement of animals, change of light setting, feed change, and/or outbreaks in neighboring herds.

122. The quality system of claim 112, wherein said at least one set of reference data comprises said threshold in the form of at least one threshold change of quantity of said biological element as a function of time from the initial event and wherein said agricultural group is a feed lot and said agricultural group location is a feed lot location or said agricultural group is an animal bedding lot and said agricultural group location is an animal bedding lot location and wherein, said initial event is selected from a change of temperature, change of location, change in humidity, change of season, mixing with another feed lot and/or breach of a biosecurity protocol.

Description

BRIEF DESCRIPTION OF THE EXAMPLES AND DRAWING

[0204] The invention is being illustrated further below in connection with selected examples and embodiments and with reference to the figures. The figures are schematic and may not be drawn to scale.

[0205] FIGS. 1a and 1b are diagrams showing a quantitative biological element determination for particles collected from animal locations of flocks of hens as a function of time.

[0206] FIG. 2 is a diagram showing the determined quantity of the 4 biological element as a function of time.

[0207] FIG. 3 is a diagram showing score of health of the digestive system of a as a function of time.

[0208] FIG. 4 is a diagram associated to example 4 and showing Vaccine concentration in air determined from particles collected as described above as a function of time.

[0209] FIG. 5 illustrates an embodiment of a quality system for determining a quality parameter of a flock of animals and/or a food lot.

[0210] FIG. 6 illustrates a process diagram of an embodiment of the method and the quality system.

[0211] FIG. 7 is a diagram associated to example 7 and showing Vaccine concentration in air determined from particles collected as described above as a function of time.

[0212] FIGS. 8a and 8b are diagrams associated to example 8 and showing Vaccine concentration in air determined from particles collected as described above as a function of time.

[0213] The quality system illustrated in FIG. 5, comprises a computer system 1, an analyzing system 2 and a collector. As indicated with the wave forms w, the computer system 1 is in data communication with a data cloud storage 4. The collector is in data communication with the analyzing system 2, Alternatively, the collector 3 and the analyzing system 2 may be integrated with each other.

[0214] In addition the computer system is in data communication with the analyzing system 2. The computer system is here illustrated as a single computer, but as described above the computer system may comprise two or more computers in data communication. The data communication may advantageously be or comprise a wireless communication.

[0215] The collector 3 is adapted for collecting particles from an animal location and/or a feed location as described above. The collection is performed as described above at selected time slots. The time of collection is transmitted to the analyzing system 2. A sample of the collected particles are analyzed using the analyzing system 2 as described above and the result is paired with the time of collection to generate a sub-sets of data, each comprising data representing the at least one quantitative, biological element determination of a sample and the time attribute of the sample. The subsets are transmitted to the computer system 1 consecutively as generated or in blocks of sub-sets.

[0216] The computer system 1 is receiving at least one set of reference data from the data cloud storage 4, where the set of reference data represents quantity of the biological element in question as a function of time correlated to the quality parameter in question as described above. The set of reference data comprises at least one threshold quality parameter of the at least one biological element as a function of time.

[0217] The computer system 1 is correlating the received consecutively sub-sets of data with the set(s) of reference data as described above and perform a determination of the quality parameter of the at least one biological element as a function of time further comprises determines the quality parameter relative to the at least one threshold quality parameter.

[0218] The computer system 1 is advantageously configured for transmitting the sub-sets of data together with the determined quality parameter to the data cloud storage 4.

[0219] The process diagram illustrated in FIG. 6, illustrates a number of steps which may be repeated e.g. with variations in collection details, preferably according to collection instructions.

[0220] In step 1 particles are collected using a collector within a selected time slot and according to collection instructions as described above. A sample of the collected particles are analyzed in step b for performing at least one quantitative, biological element determination using an analyzing system.

[0221] The resulting determination is transmitted to the computer system in step c, as a sub-set of data also comprising a time attribute representing a time of collection

[0222] The sub-set of data received by the computer system is in step d collected with previous received sub-set of data if any.

[0223] In step e the computer system is acquiring reference data from the data cloud storage. Step e may be performed anywhere in the series of steps or it may be omitted if the computer system has already received reference data or stores reference data itself.

[0224] In step of the computer system determines the quality parameter as it is at the time of collecting the latest analyzed particles.

[0225] In step g the computer system determines if the quality parameter is outside a threshold.

[0226] In step h the computer system displays the result and optional suggestions e.g. as described above. And the steps are repeated. In the illustrated step z, the computer system transmits data comprising one or more sub-sets together with determined quality parameter(s) to the data cloud storage.

[0227] These steps may be omitted in one or more series of steps and/or it may be performed at any time in the series of steps.

EXAMPLE 1

Correlations when Monitoring of Several Biological Elements

[0228] In this example concentration of a number of biological elements are determined at consecutive time slots to follow the development of these concentrations over time. The biological element are 7 different microbiological organisms (bacteria and virus). The time slots were 4 hours and the particle collection were performed once per month.

[0229] Surveillance of different microbiological organism may reveal an emerging infection spreading in a flock or herd. The surveillance program was conducted over a period of 6 months in 3 flocks of animals, namely three poultry houses with laying hens.

[0230] The quantitative recordings of one of the biological elements, namely E. coli in the three different poultry houses recorded over a period of 6 months is shown in FIG. 1a, where the series 1, represents poultry house 1, series 2 represents poultry house 2 and series 3, represents poultry house 3.

[0231] In two of the houses (poultry house 1 and poultry house 3) the concentration of E. coli in the air inside the houses continuously increases over time.

[0232] Whereas, in the last house (poultry house 2) the concentration remained constant over time (it even showed a slight decrease). In the two houses where the concentration of the E. coli where increasing a wild strain of the infectious bronchitis virus was discovered in the air samples collected in June.

[0233] These measurements illustrate the use of the E. coli concentration as an indicator of the overall health of a poultry flock. In such a setup an increase in the E. coli concentration should encourage the producer to investigate the source of this increase, which may be both diseases related or metabolic related.

[0234] Processing of the data by using reference data may be advantageous for fast and accurate discovering a drop in a quality parameter especially because the quality parameter will vary naturally over time and the lifespan of the animals.

[0235] The raw E. coli data is shown in FIG. 1a, in which the natural short-term fluctuation of the pathogen pressure in the form of the quantity of the E. coli that to a certain extent will occur in the animal location, clouds the long-term tendencies of the E. coli pressure. A simple sliding average applied to the data as shown in FIG. 1b may limit the effects of the short-term variation and allow the long-term tendencies to become visible.

[0236] A threshold level “T” is illustrated in both FIG. 1a and FIG. 1b. This threshold level “T” is obtained from poultry houses of same type, i.e. similar size, number of and/or age of poultry.

[0237] As it can be seen on both FIG. 1a and FIG. 1 b, the E. coli concentration in poultry house 2 was increasing the threshold level “T” already in early May.

[0238] Thus had the system of the invention been applied, the farmer would have been alerted already in early May that an undesired level of E. coli was under development and likely the wild strain of the infectious bronchitis virus would have been found several weeks earlier.

[0239] In a first variation thereof, a threshold level “T” may be determined by professionals preferably base on their knowledge of which level supports fast growth and which do not, which level supports poultry well-being and which do not.

[0240] In a second variation thereof, a threshold level “T” may be obtained by historical data from the present farm and other like farms combined with information on other quality parameters collected from these farms at the same time. From these historical data it may be possible to derive the level of for instance E. coli in the poultry houses were the other quality parameters typically is also good. In such a situation if the E. coli concentration raises above the threshold it is indicative that some of the other quality parameters will likely also soon start to change.

EXAMPLE 2

The Health of the Digestive System of a Flock

[0241] In this example particles are collected in a hen house with a flock of hens (25.000-100.000 pr. house). The collection is performed once every 5th day in a time slot between 10:00 and 12:00. Collecting time is 5 minutes.

[0242] Quantitative determinations of 4 different biological elements are performed.

[0243] The 4 different biological element are 4 different types of gut microbiota. The results are shown in FIG. 2.

[0244] Based on the relationship between the concentrations and the relative change over time the health of the digestive system of the flock can be monitored. In this way probiotic treatment may be initiated if some of the parameters drops, e,g. drops faster than a threshold or falls outside a threshold.

[0245] FIG. 3 shows a comparison between the biological element with ID 1 and the biological element with ID 4. The biological element with ID 1 is believed to have positive effect on digestive health, whereas the biological element with ID 4 is believed to have negative. By dividing the biological element-ID 1 by the biological element-ID 4 a helpful quality parameter and a threshold therefor may be obtained.

[0246] In addition FIG. 3 illustrates digestive health scores with a simple value based reference threshold level “T”. When the value break the threshold it indicates that there may be some underlying issue in the flock that should be further investigated either by traditional means or by analysis of curves from other quality parameters to provide an indication of the underlying issues.

[0247] By comparing the determined quantity of the 4 biological element with reference data, which may include threshold data, one or more quality parameter may be determined. The result may be communicated to the producers along with recommendations on which actions may be taken to increase the ratio and health of the flock and hence increase productivity of the production.

EXAMPLE 3

Production Optimization

[0248] In this example a panel of different production related pathogens (biological elements), both directly and in directly disease related are determined from particles collected in an animal location as a function of time. Based on previous data analysis (reference data) both from the specific farm but also on data from other farms of same type of animal location and/or type of flock of animals in the area, country or even worldwide. Specific patterns in the change of concentration between these reference data are recognized so that the AI or numerical algorithm can inform that a rise in one of the pathogens is most likely followed by a rise in second pathogen and hence probiotic treatment may be initiated at a very early stage to avoid this risk.

EXAMPLE 4

Vaccination Protection and Strategy

[0249] In this example the quantitative biological element determinations of particles collected over time as described above is used to validate that the vaccination procedure was conducted correctly and that the flock of animals is protected against the relevant disease. In such an application the biological element determined includes the live vaccine on the particles collected from the air inside the location comprising the flock of animals. The particles are collected at specific times according to given time slots post vaccination, to verify that the vaccine concentration in the air follows the expected trajectory indicating a successful vaccination procedure. Should only a minor fraction of the flock have received the vaccination, the remaining flock will remain naive and receive the vaccine from already vaccinated animals, and the concentration of the vaccine in the air, may remain elevated over longer times. Alternatively, if the vaccine does not spread to the naïve animals e.g. birds, but only a fraction of the birds received the vaccine the level may not exceed a threshold level, indicating that only a fraction of the population is prober protected. An

[0250] Illustration of such situation can be seen in FIG. 4, where the noncomplete vaccinated flock excrete less of the vaccine in the peak days and the levels does not fall off as rapidly, as the case for the successfully vaccinated flock.

[0251] In a simple application the concentration of the vaccine on day 4 divided by the vaccine concentration on day 8 may provide the user with valuable information about the vaccination success.

EXAMPLE 5

Vaccination Protection and Strategy

[0252] In a variation of example 4, the data generated by the quality system is used to qualify the decisions related to vaccination procedures in between flocks of animals or rotations of flocks of animals e.g. chicken in a broiler production. In such an application, vaccine may be given to the subsequent flock of animals at the animal location if any signs of an emerging disease are present in the current flock of animals. If signs show that for instance infectious bursal disease or infectious bronchitis virus is emerging in the current flock of animals, vaccination of the subsequent flock or flocks of animals may be initiated on an informed basis.

EXAMPLE 6

Vaccination Protection and Strategy

[0253] Likewise, the data from the quality system may be used to ensure that the flocks of animals is healthy enough at the vaccination time so that the vaccination strategy may be successful. If for instance infectious bursal disease virus was present in the flock of animal e.g. birds at the time of vaccination, such an infection may affect the immune system of the birds. This may limit the effect of a vaccination procedure and hence may result in not sufficiently protected or even naive birds in the flock.

EXAMPLE 7

Vaccination Protection and Strategy

[0254] Chickens of a flock of chickens in a chicken house were vaccinated for infectious bronchitis virus (IBV) as one day old and for infectious bursal disease virus (IBDV) at day 20. In this example the vaccines were administered by spray and drinking water respectively. Air samples were collected throughout the production cycle as seen in FIG. 7. The vertical axis is a linear scale of the vaccine concentration in air samples of particles collected inside the poultry house and the horizontal axis is the age of broilers in days from IBV vaccination. The shape and the width of the bell shaped vaccine response curves can be used to derive the effectiveness of the vaccine. If for instance not all broilers was targeted by the original vaccine one would expect an extended curve. Furthermore the fact that the vaccine can be found in the air samples is also indicative that the vaccine reached the broilers and did in fact reproduce therein as intended—otherwise it would not be possible to find it in the air. Especially the fact that the vaccine is found in the air starting from 4-5 days post vaccination indicates that the vaccine in fact reached the broilers. If the vaccine was compromised by some means and lost its ability to infect the chickens and activate the immune response it would not be expected to see the vaccine in the air. Such a concentration in the air is only possible where the vaccine were reproduced in the broilers as intended.

[0255] In a variation of this example a number of the chickens, preferably at least 50% of the chickens of the flock of chickens in a chicken house is vaccinated by injections.

EXAMPLE 8

Vaccination Protection and Strategy

[0256] Chickens of flocks of chickens (broilers) in three chicken houses, house 1, house 2 and house 3, were vaccinated for infectious bursal disease virus (IBDV) at day 20.

[0257] From day 11 particle samples were collected from each chicken house once every other day in a time slot between 10:00 and 12:00. Collecting time was about 10 minutes.

[0258] Determinations of vaccine concentration were determined from each sample.

[0259] A plot of the results from chicken house 1, 2 and 3 are shown in FIG. 8a.

[0260] FIG. 8a also show upper and lower thresholds curves for the vaccine concentration.

[0261] This upper and lower thresholds curves for the vaccine concentration has been determined from measurements obtained from previous IBVD vaccinations both at the specific location and from other related locations i.e. chicken houses of same type (ie production form and race).

[0262] The lower threshold is set for ensuring an effective vaccination of the entire flock of chicken. If the vaccine concentration in a chicken house drops below this lower threshold, it indicates that the vaccine may not have been fully effective, for example if the distributed vaccine was compromised and did not work and/or a too low percentage of the chickens may have been sufficiently vaccinated to reach flock immunity. A supplementary vaccination may then be recommended.

[0263] The upper threshold is set for observing any undesired infections of the infectious bursal disease virus or presence of wild strains of infectious bursal disease viruses. As long as the vaccine concentration in a chicken house stays below the upper threshold, there is no need for further analysis (sequencing) to determine the virus variant or optional mutations.

[0264] If the vaccine concentration in a chicken house exceeds the upper threshold, this may indicate underlying issues in the house and or the vaccination procedure. Depending on when and how the threshold curves are broken it may be caused by different issues. If for instance vaccine curves are elongated or have a double top it may indicate that only a fraction of the birds were targeted by the initial vaccine and the remaining birds are affected from these birds. On the other hand If the vaccine curves follow the expected bell curve in the beginning but at the end starts to increase this may indicate that a wild strain is existing in the house and developing beneath the vaccine strain.

[0265] As it can be seen the upper and lower thresholds curves varies as a function of time from the time of vaccination.

[0266] The upper and lower thresholds curves may dynamically be updated from determinations of concentration of infectious bursal disease virus in related locations e.g. from determinations of concentration of infectious bursal disease virus obtained in other same type chicken houses in which the quality system according to the invention has been applied and where the determinations is uploaded to a data cloud storage e.g. as described above.

[0267] The concentration determinations of the four chicken houses may in the same way be feed back into the system for updating the threshold data. This may e.g. be provide by uploading the determinations from the four houses to the data cloud storage.

[0268] In FIG. 8b the results from chicken house 4 is plotted together with the upper and lower thresholds curves. Here it can be seen that around day 52 the determined of concentration of infectious bursal disease virus exceeds the upper threshold. Analysis showed that this was caused by a wild strain of infectious bursal disease virus. This information may be uploaded to the data cloud storage together with the determined of concentration of infectious bursal disease virus for house 4.

EXAMPLE 9

Surveillance of a Feed Lot

[0269] The quality system is in this example used to monitor a feed lot comprising feed for animals. The feed lot may be monitored using the method described above at one or more feed lot locations in the production line e.g. at any point were the materials is handled and dust may be produced.

[0270] When importing goods by ship the entire load on the ships may be monitored at different locations during unloading to detect any presence of harmful or zoonotic pathogens present in the raw material feed lot to ensure proper handling at the production plant.

[0271] At the arrival at the feed production facilities the raw material feed lot may be monitored during unloading for the presence of the most common and/or harmful bacteria, virus, spores or other microbiological components to ensure that the harmful organism does not reach the farmers.

[0272] The feed lot may likewise be monitored in the mixing of the materials in the actual production of the feed lot. Particles may be at specific intervals or at specific times for instance during mixing and/or heating.