Breeding system for accurately measuring individual feed conversion rate under goose stress-free state based on Internet of Things technology and application

Abstract

The invention discloses a breeding system for accurately measuring the individual feed conversion rate in a goose stress-free state based on the Internet of Things technology and application. According to the breeding system, the free feed intake amount of each goose individual can be accurately measured under the state of no stress in goose group feeding, the measured individual feed consumption amount is accurate, the breeding effect of the breeding geese can be rapidly improved, the breeding progress is accelerated, the feed conversion rate of the selected goose individuals is increased by 10%-15%, the problem of feed shortage is greatly relieved, and the breeding quality of the geese is improved. And new kinetic energy is provided for high-quality development of the waterfowl industry.

Description

Technical Field

[0001] The present invention relates to a goose individual feed conversion rate accurate measurement breeding system under a stress-free state based on the Internet of Things technology and its application, belonging to the technical field of goose breeding. Background Art

[0002] As a characteristic industry in my country, meat geese account for more than 80% of the world's total annual output, ranking first in the world. Improving the production level and efficiency of my country's goose industry is the only way to meet the effective supply of livestock products and diversified market demand. The main ways to improve production levels and production efficiency are intelligence and scale. However, compared with chickens and ducks, geese have special living habits. Breeding geese in cages is too stressful, and large-scale cage breeding cannot be carried out. The results of forced cage breeding are also difficult to reflect the true growth level and performance of individual breeding geese. To improve the production performance of geese, accurately measuring the growth data of geese is the most critical task. In the process of meat goose breeding, the accurate measurement and breeding of the feed conversion efficiency of each goose is the top priority to improve the growth performance and production efficiency of geese.

[0003] In order to solve the problem of slow progress in meat goose breeding, it is necessary to accurately measure the growth performance of breeding geese, timely discover and eliminate breeding geese with low feed conversion rate and slow growth rate, and screen out high feed conversion groups. The existing poultry feed conversion rate measurement devices are mainly focused on the research of the measurement method of chickens and ducks raised in individual cages. Most of them use manual measurement to weigh the weight of each poultry when it is individually caged, give it a fixed weight of feed during feeding, and measure the specific weight gain and feed consumption at the end of each measurement stage to obtain the feed consumption and weight gain ratio. Errors and mistakes are inevitable in the processing of huge breeding data, which affects statistical analysis; and with the increase in labor costs, it leads to a certain degree of waste of time, financial resources, and material resources, which is not conducive to the accurate measurement of the feed conversion rate of individual poultry. For geese, they have strong group habits, high cost of raising a single cage, inaccurate measurement results, and cannot reflect the best growth performance of geese. Therefore, it is impossible to measure the feed conversion data of geese according to the measurement method of chickens and ducks.

[0004] The feed conversion rate directly affects the breeding cost and economic benefits. The low feed conversion rate of geese not only makes the economic benefits of the meat goose industry low, but also makes the economic cost of raising meat geese generally high, which also makes the development of the meat goose breeding industry stagnant. To solve this problem, it is necessary to carry out large-scale and intensive breeding of the production performance of meat geese, timely discover and eliminate meat geese with low feed conversion rate, and select meat geese with high feed conversion rate. However, it is currently impossible to accurately record the feed intake and weight gain of group-raised meat geese in real time, which limits the breeding process of high feed conversion rate breeding geese.

[0005] Therefore, the key to improving goose breeding efficiency is to accurately measure the amount of feed each goose consumes freely each time under the goose's natural growth state without stress, and calculate the precise feed conversion of each goose when it is released. Summary of the invention

[0006] Purpose of the invention: The purpose of the present invention is to provide a system for accurately measuring and breeding the individual feed conversion rate of geese under stress-free conditions based on Internet of Things technology and its application.

[0007] Technical solution: The present invention provides a breeding system for accurately measuring individual feed conversion rate of geese in a stress-free state based on the Internet of Things technology. The breeding system includes a plurality of goose identity information recording devices, goose individual limiting feed devices, feed precision weighing devices and a signal data processing module;

[0008] The goose identity information recording device is used to record and store the individual identity information of the goose;

[0009] The goose individual limiting feeding device comprises two limiting columns, a crossbeam for fixing the limiting columns and a base; the limiting columns are detachably mounted on both sides of the base, and a space is reserved in the base for placing an identifier that matches the goose identity information recording device and is used to read the individual identity information of the goose;

[0010] The feed precision weighing device comprises a weighing device with a TCP protocol, a barrel bracket is fixedly arranged on the weighing device, a feed trough is arranged in the barrel bracket and on the weighing device, and an autonomous unloading barrel is arranged on the barrel bracket;

[0011] The signal data processing module is used to receive and process data transmitted by the goose identity information recording device, the identifier and the feed precision weighing device.

[0012] Furthermore, the goose identity information recording device is an RFID ID card anklet, which is worn on the goose toe bone.

[0013] Furthermore, the identifier is an RFID radio frequency identifier.

[0014] Furthermore, the goose individual limiting feeding device adjusts the distance between the two limiting columns according to the chest width of the goose at different stages.

[0015] Furthermore, the barrel bracket is provided with a fence except for the side facing the goose individual limiting feed device.

[0016] Furthermore, the side of the barrel bracket facing the goose individual limiting feed device may not be provided with a fence or may be provided with a fence with openings.

[0017] The present invention also provides application of the breeding system in breeding geese with high growth performance and high production efficiency.

[0018] The present invention also provides a method for accurately measuring and breeding individual feed conversion rates of geese in a stress-free state based on the Internet of Things technology, comprising the following steps:

[0019] (1) Wearing a goose identity information recording device on the goose's toe bone, manually measuring the initial weight of each goose, and recording it as the entry weight; inputting the goose's identity number and entry weight into the signal data processing module;

[0020] (2) After the goose enters the individual limited feeding device, the identifier senses the signal and reads the information in the goose identity information recording device and uploads it to the signal data processing module. The signal data processing module sends a command signal, and the feed precision weighing device starts to dynamically measure and record the remaining amount of feed in the special feed trough at a frequency of 3-8 times per second, and transmits the data to the signal data processing module; the total feeding time of the goose and the initial weight of the feed when the goose enters the individual limited feeding device are recorded, and then the above data are transmitted to the signal data processing module;

[0021] (3) After the goose leaves the individual goose limiting feeding device, the identifier senses that the signal disappears, immediately records the feed weight, and transmits the data to the signal data processing module. The signal data processing module calculates the feed intake of this time based on the feed weight when the goose enters the individual goose limiting feeding device and the feed weight when it leaves, and compiles the feed intake of each time into a feeding record table;

[0022] (4) When the geese are raised to 56 to 70 days of age, the weight of each goose is measured and recorded as the market weight. The weight is input into the signal data processing module, which calculates the feed-to-meat ratio of each goose based on the feeding record, entry and market weight of each goose, and sorts them by size. Goose breeds with a high feed-to-meat ratio are high-quality goose breeds.

[0023] Furthermore, the feed-to-meat ratio is calculated as: total feed consumption (kg) / total body weight gain (kg).

[0024] Furthermore, if the feed intake of each goose in step (3) is within the error range, that is, within the normal feed intake range of the goose, the data is recorded normally; if the data is not within the error range, it is determined to be abnormal weight loss / abnormal weight gain of feed intake, and if this abnormality is the first abnormal record of the goose, the data is initialized; if this abnormality is not the first abnormal record of the goose, check whether the feed weight of the individual limit feed device of the goose when the goose enters is consistent with the feed weight of other geese on the device when they left last time, and if it does not match, it is manually modified.

[0025] Beneficial effects: Compared with the prior art, the present invention has the following outstanding significant advantages: the breeding system of the present application can accurately measure the amount of feed that each goose can eat freely under stress-free conditions in goose group breeding. The measured individual feed consumption is accurate, which can quickly improve the breeding effect of breeding geese and accelerate the progress of breeding. The feed conversion rate of the selected goose breeds will be increased by 10%-15%, which greatly alleviates the problem of feed shortage and provides new impetus for the high-quality development of the goose industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a schematic diagram of the structure of the device for limiting the feeding of individual geese;

[0027] Figure 2 This is a schematic diagram of the structure of a feed precision weighing device;

[0028] Figure 3 It is a top view of the device for limiting the feeding of individual geese and the device for accurately weighing the feed;

[0029] Figure 4 It is a breeding system for accurate measurement of individual feed conversion rate of geese under stress-free state based on Internet of Things technology;

[0030] Figure 5 It is an illustration of the practical application of the breeding system of the present invention. DETAILED DESCRIPTION

[0031] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0032] Example 1

[0033] The system for accurately measuring and breeding individual feed conversion rate of geese in a stress-free state based on the Internet of Things technology of the present invention specifically comprises a goose identity information recording device, a goose individual limiting feed device, a feed accurate weighing device and a signal data processing module;

[0034] The goose identity information recording device is used to record and store the individual identity information of the goose; specifically, it is an RFID ID card anklet, which is worn on the goose's toe bone;

[0035] The goose individual limiting feed device ( Figure 1 ) comprises two limit posts, a crossbeam for fixing the limit posts and a base; the limit posts are installed on both sides of the base, and a space is reserved in the base for placing an identifier that matches the goose identity information recording device and is used to read the individual identity information of the goose; the identifier is specifically an RFID radio frequency identifier;

[0036] The goose individual limit feed device adjusts the distance between the two limit posts according to the chest width of the goose at different stages, and can also adjust the height of the limit posts according to actual application requirements;

[0037] The feed precision weighing device ( Figure 2 ) includes a weighing device with a TCP protocol, a barrel bracket is fixedly arranged on the weighing device, a feed trough is placed in the barrel bracket and on the weighing device, and an autonomous feeding barrel is arranged on the barrel bracket; the barrel bracket is provided with a fence except for the side facing the individual goose limiting feed device, and the side of the barrel bracket facing the individual goose limiting feed device may not be provided with a fence or may be provided with a fence with an opening;

[0038] The top view of the goose individual feed limiting device and feed precision weighing device is as follows Figure 3 As shown, the feed precision weighing device is placed in front of the goose individual limiting feed device.

[0039] The signal data processing module is used to receive and process data transmitted by the goose identity information recording device, the identifier and the feed precision weighing device.

[0040] The schematic diagram of the above-mentioned IoT-based goose individual feed conversion rate accurate measurement breeding system under stress-free state is as follows Figure 4 shown.

[0041] Example 2

[0042] A method for accurately measuring the feed conversion rate of geese in a stress-free state based on the Internet of Things technology (in this example, Yangzhou geese are used as experimental objects, purchased from Yangzhou Tiange Goose Industry Development Co., Ltd., 28 days old), comprising the following steps:

[0043] (1) Wear the goose identity information recording device (RFID ID card anklet) on the goose toe bone, measure the initial weight of each goose, and input the goose identity number and initial weight into the signal data processing module;

[0044] An example of information recorded on an RFID ID card anklet is: 01001006, which refers to the first house, the first pen, the sixth goose. Each goose has a unique identity information number.

[0045] (2) After the goose enters the individual limited feeding device, the RFID radio frequency identifier senses the RFID signal and reads the information in the goose identity information recording device and uploads it to the signal data processing module. The signal data processing module sends a command signal, and the feed precision weighing device starts to dynamically measure and record the remaining feed in the special feed trough at a frequency of 3-8 times per second, and transmits the data to the signal data processing module; the total feeding time of the goose, the weight when entering and leaving the pen, and the weight of the feed when entering the pen are recorded, and then the above data are transmitted to the signal data processing module;

[0046] (3) After the goose has finished eating and leaves the individual goose limiting feeding device, the RFID radio frequency identifier senses that the signal disappears, and immediately records the feed weight of the goose when it leaves the pen, and transmits the data to the signal data processing module. The signal data processing module calculates the feed intake of this time based on the feed weight of the goose when it enters the pen and the feed weight when it leaves the pen, and compiles the feed intake of each time into a feeding record table;

[0047] The system sets a minimum feed amount. If it is lower than the set number, the system will remind you to add feed and fill it up in time.

[0048] (4) When the goose is raised to 56 days of age, the weight of each goose is measured and input into the signal data processing module. The signal data processing module calculates the feed-to-meat ratio of each goose based on the feeding record, entry and exit weight of each goose, and sorts them by size. Goose breeds with a high feed-to-meat ratio are high-quality goose breeds.

[0049] A total of 150 Yangzhou geese were raised and tested, with 50 geese in each group and 50 geese in each pen. The first and second pen used the breeding system of this test (feed-to-meat ratio = total feed consumed kg / total weight gain kg), and the third pen used the conventional large group feeding method (the feed-to-meat ratio was calculated based on the average feed-to-meat ratio of the geese calculated based on the total feed).

[0050] First, the weight of each goose at 28 days old was measured. The first two pens were equipped with corresponding electronic leg rings, and each pen was equipped with a measuring machine for 10-15 geese. The third pen was free-range and placed with ordinary feed troughs.

[0051] From the 28th day to the 56th day, a total of 28 days of testing were performed, and the results are as follows:

[0052]

[0053] Note: The numbers with different letters are significantly different, p<0.05.

[0054] 100 geese with electronic numbers were sorted according to the feed-to-meat ratio. The smaller the feed-to-meat ratio, the less feed is needed to convert feed into goose meat, the lower the breeding cost, and the better the economic benefits. Therefore, according to the 30% selection pressure, we selected the geese with the top 30% feed-to-meat ratio as breeding geese for breeding, and the specific results are as follows.

[0055]

[0056]

[0057] From the results, it can be seen that the average feed-to-meat ratio of the 33 geese in the top 30% is 18% higher than that of free-range geese, and 14% higher than the average of accurately measured geese. Therefore, this system and method can play a very important role in improving the feed conversion rate of Yangzhou goose breeders. Through the use of this system and equipment, feed waste can be reduced, saving production and breeding costs for enterprises.

Claims

1. A system for accurately measuring and breeding individual feed conversion rates of geese in a stress-free state based on Internet of Things technology, characterized in that: The breeding system includes several goose identity information recording devices, goose individual limiting feed devices, feed precision weighing device devices and a signal data processing module; The goose identity information recording device is used to record and store the individual identity information of the goose; The goose individual limiting feeding device comprises two limiting columns, a crossbeam for fixing the limiting columns and a base; the limiting columns are detachably mounted on both sides of the base, and a space is reserved in the base for placing an identifier that matches the goose identity information recording device and is used to read the individual identity information of the goose; The feed precision weighing device comprises a weighing device with a TCP protocol, a barrel bracket is fixedly arranged on the weighing device, a feed trough is arranged in the barrel bracket and on the weighing device, and an autonomous unloading barrel is arranged on the barrel bracket; The signal data processing module is used to receive and process data transmitted by the goose identity information recording device, the identifier and the feed precision weighing device.

2. The breeding system according to claim 1, characterized in that: The goose identity information recording device is an RFID ID card anklet, which is worn on the goose toe bone.

3. The breeding system according to claim 1, characterized in that: The identifier is an RFID radio frequency identifier.

4. The breeding system according to claim 1, characterized in that: The goose individual limiting feeding device adjusts the distance between the two limiting columns according to the chest width of the goose at different stages.

5. The breeding system according to claim 1, characterized in that: The barrel bracket is provided with a fence except for one side facing the goose individual limiting feed device.

6. The breeding system according to claim 1, characterized in that: The side of the barrel bracket facing the goose individual limiting feed device may not be provided with a fence or may be provided with a fence with an opening.

7. Use of the breeding system according to any one of claims 1 to 6 in breeding geese with high growth performance and high production efficiency.

8. A method for accurately measuring the feed conversion rate of geese in a stress-free state based on the Internet of Things technology, characterized in that: The following steps are involved: (1) Wearing a goose identity information recording device on the goose's toe bone, manually measuring the initial weight of each goose, and recording it as the entry weight; inputting the goose's identity number and entry weight into the signal data processing module; (2) After the goose enters the individual limited feeding device, the identifier senses the signal and reads the information in the goose identity information recording device and uploads it to the signal data processing module. The signal data processing module sends a command signal, and the feed precision weighing device starts to dynamically measure and record the remaining amount of feed in the special feed trough at a frequency of 3-8 times per second, and transmits the data to the signal data processing module; the total feeding time of the goose and the initial weight of the feed when the goose enters the individual limited feeding device are recorded, and then the above data are transmitted to the signal data processing module; (3) After the goose leaves the individual limited feeding device, the identifier senses that the signal disappears, immediately records the weight of the goose feed, and transmits the data to the signal data processing module. The signal data processing module calculates the feed intake of this time based on the feed weight of the goose when it enters the individual limited feeding device and the feed weight when it leaves, and compiles the feed intake of each time into a feed intake record table; (4) When the geese are raised to 56 to 70 days of age, the weight of each goose is measured and recorded as the market weight. The weight is input into the signal data processing module, which calculates the feed-to-meat ratio of each goose based on the feeding record, entry and market weight of each goose, and sorts them by size. The goose with the smaller feed-to-meat ratio is identified as a high-quality individual.

9. The breeding method according to claim 8, characterized in that: The calculation formula for the feed-to-meat ratio is total feed consumption (kg) / total body weight gain (kg).

10. The breeding method according to claim 8, characterized in that: If the feed intake of each goose in step (3) is within the error range, that is, within the normal feed intake range of the goose, the data is recorded normally; if the data is not within the error range, it is determined to be abnormal weight loss / abnormal weight gain of feed intake. If this abnormality is the first abnormal record of the goose, the data is initialized; if this abnormality is not the first abnormal record of the goose, check whether the feed weight of the individual limit feed device of the goose when the goose enters is consistent with the feed weight of other geese on the device when they left last time. If it does not match, it is manually modified. If it matches but the feed intake is abnormal, the data is deleted.

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