scholarly journals Repeatability and frequency of in-paddock sheep walk-over weights: implications for individual animal management

2014 ◽  
Vol 54 (2) ◽  
pp. 207 ◽  
Author(s):  
D. J. Brown ◽  
D. B. Savage ◽  
G. N. Hinch
Keyword(s):  
Radio Frequency Identification ◽  
Null Hypothesis ◽  
Average Reference ◽  
Animal Management ◽  
Data Points ◽  
Frequency Identification ◽  
The Mean ◽  
Gut Fill ◽  
On Farm ◽  
Over Time

Sheep liveweight is an indicator of nutritional status, and its measure may be used as an aid to nutritional management. When walk-over weighing (WOW), a remote weighing concept for grazing sheep, is combined with radio frequency identification (RFID), resulting ‘RFID-linked WOW’ data may enable the liveweight of individual sheep to be tracked over time. We investigated whether RFID-linked WOW data is sufficiently repeatable and frequent to generate individual liveweight estimates with 95% confidence intervals (95% CI) of <2 kg (a sufficient level of error to account for fluctuating gut fill) for a flock within timeframes suitable for management (1-day and 5-day timeframes). Four flocks of sheep were used to generate RFID-linked WOW datasets. RFID-linked WOW data were organised into three groups: raw (unfiltered), coarse filtered (remove all sheep-weights outside the flock’s liveweight range), and fine filtered (remove all sheep-weights outside a 25% range of a recent flock average reference liveweight). The repeatability of raw (unfiltered) RFID-linked WOW data was low (0.20), while a coarse (0.46) and fine (0.76) data filter improved repeatability. The 95% CI of raw RFID-linked WOW data was 27 kg, and was decreased by a coarse (11 kg) and fine (6 kg) data filter. Increasing the number of raw, coarse and fine-filtered data points to 190, 30 and 12 sheep-weights, respectively, decreased the 95% CI to <2 kg. The mean cumulative percentage of sheep achieving >11 fine-filtered RFID-linked WOW sheep-weights within a 1-day and 5-day timeframe was 0 and 10%, respectively. The null hypothesis was accepted: RFID-linked WOW data had low repeatability and was unable to generate liveweight estimates with a 95% CI of less than 2 kg within a suitable timeframe. Therefore, at this stage, RFID-linked WOW is not recommended for on-farm decision making of individual sheep.

A comparative study of RFID adoption patterns in retail

2021 ◽  
pp. 1-20
Author(s):  
Narges Kasiri ◽  
G. Scott Erickson ◽  
Gerd Wolfram
Keyword(s):  
Comparative Study ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Structural Model ◽  
Slow Pace ◽  
The Us ◽  
Frequency Identification ◽  
Insight Into ◽  
Current Stage ◽  
Over Time

Radio frequency identification (RFID) has been viewed as a promising technology for quite some time. Initially developed a couple of decades ago, the technology has been accompanied by predictions of imminent widespread adoption since its beginnings. A majority of retailers and other users are now using or planning to use the technology. This paper employs a combination of the technology-organization-environment (TOE) model and the 3-S (substitution, scale, structural) model to analyze the long journey of RFID adoption in retail. Top retail executives in the US and Europe were interviewed to investigate RFID adoption patterns based on differences in technological, organizational, and environmental circumstances. As the retail industry is moving into a post-adoption era, these results demonstrate the current stage of retail RFID adoption, identify factors playing important roles over time as motivators or impediments, and provide some insight into the slow pace of adoption.

58 RADIO-FREQUENCY IDENTIFICATION INTELI-STRAWS: GAMETES AND EMBRYO PACKAGING, STORAGE, AND INFORMATION RECOVERY

2017 ◽  
Vol 29 (1) ◽  
pp. 136
Author(s):  
M. E. Kjelland ◽  
T. Loper ◽  
C. Woodley ◽  
T. M. Swannack ◽  
T. K. Stroud ◽  
...  
Keyword(s):  
Radio Frequency ◽  
Liquid Nitrogen ◽  
Radio Frequency Identification ◽  
Exact Test ◽  
Information Recovery ◽  
Cold Tolerant ◽  
Frequency Identification ◽  
The Mean ◽  
Extreme Cold ◽  
And Control

The assisted reproduction industry involving sales and services for gametes and embryos for domestic animals of commercial value is a large market totaling millions of dollars annually. The objective of this study was to develop and test gamete and embryo packaging—Inteli-Straws (I-S) equipped with radio-frequency identification (RFID) technology. Specifically, French straws (0.25 and 0.5 mL) were modified to include extreme cold-tolerant RFID microchips. Two groups of I-S were formed: Group (G)1: RFID chips that were autoclaved (n = 49), and G2: RFID chips that were not autoclaved (n = 47). Both groups had a control that was not exposed to liquid nitrogen (LN). Each group was exposed to LN up to 4 times: 2 slow freezes first and then 2 fast (i.e. vitrification) freezes, and I-S RFID chip survival was determined. I-S detection and readability (non-autoclaved) was also measured, placing I-S just above LN (in vapors, n = 43) or just below LN (n = 38). Statistical differences (α = 0.05) were determined using Fisher’s exact test. The results between G1 and G2 were not significantly different (P = 0.108) after 4 rounds of cryopreservation (and thawing). For G1, 98% (48/49) of the I-S RFID chips remained operational, and control and treatment were not significantly different (P = 1.000). For G2, 89.4% (42/47) of the autoclaved RFID chips remained operational, and control and treatment not significantly different (P = 0.099). RFID chip readability results; that is, the ability to detect the I-S versus not able to detect the I-S, comparing placement just above liquid nitrogen (LN) versus the placement just below LN were not significantly different (P = 0.105). Notably, detection differences varied within each group, with I-S in G1 (mean = 9.5; SD = 3.5 cm) readable at a larger distance, 5.2 cm farther than the mean of G2 (mean = 4.3; SD = 1.9 cm). During AI or embryo transfer (ET), a technician may not clearly identify the label or colour of straw, may incorrectly record the information, or may take more time than desirable to record it. Increased exposure times may lead to decreased viability of gametes and embryos. The results show that by using the I-S, one may quickly scan the straw within LN or LN vapors, thereby automatically detecting information and even uploading it to a database (e.g. scanner sophistication). We are not aware of comparable device to I-S for locating and retrieving associated information without removing the gamete/embryo packaging from LN or LN vapors; unlike traditionally labelled straws (e.g. laser etched or ink labels). Also, for AI and ET, the I-S can be quickly scanned and the straw information automatically detected and uploaded to a database.

scholarly journals Effects of Advanced Producer Training and Technology on Cattle Mortality During Dystocia

2020 ◽  
Vol 8 (4) ◽  
pp. 350
Author(s):  
Kimberly Inman ◽  
Clint Ary ◽  
Will Bird ◽  
Joey Mehlhorn ◽  
Jason Roberts
Keyword(s):  
Management Practices ◽  
Herd Size ◽  
Reproductive Age ◽  
Multiple Data ◽  
Detection Technology ◽  
Data Points ◽  
The Mean ◽  
Cattle Reproduction ◽  
On Farm ◽  
Mortality Percentage

This study was conducted to investigate what variables may be more significant on farms in reducing both fetal and maternal mortality due to dystocia. Data on risk factors likely to impact cattle mortality were collected from a written herd questionnaire to determine farm management practices linked to cattle reproduction and the mortality related to dystocia. The questionnaire contained 16 questions grouped in the study. The survey contained qualitative and quantitative questions.  The design utilized multiple data points with calving factors, age of dam, birth weight, sex of calf, breeds, heifers, cows, body condition, advanced beef producer training of recognition of impending labor, calf death, and dam death. Twenty-seven livestock producers from the state of Tennessee completed the questionnaire. The mean average herd size included 39 cows at reproductive age. The results showed labor detection technology and advanced training helped to reduce the herd mortality percentage. Cattle producers who place value on educating themselves and their workers can make their farms more efficient and profitable by making better on-farm decisions and implementing available technologies.

scholarly journals Depth Image Selection Based on Posture for Calf Body Weight Estimation

2021 ◽  
Vol 9 (1) ◽  
pp. 20
Author(s):  
Yuki Yamamoto ◽  
Takenao Ohkawa ◽  
Chikara Ohta ◽  
Kenji Oyama ◽  
Ryo Nishide
Keyword(s):  
Body Weight ◽  
Radio Frequency Identification ◽  
Selection Method ◽  
Contour Detection ◽  
Depth Image ◽  
Percentage Error ◽  
Weight Estimation ◽  
Depth Images ◽  
Frequency Identification ◽  
The Mean

We are developing a system to estimate body weight using calf depth images taken in a loose barn. For this purpose, depth images should be taken from the side, without calves overlapping and without their backs bent. However, most of the depth images that are taken successively and automatically do not satisfy these conditions. Therefore, we need to select only the depth images that match these conditions, as to take many images as possible. The existing method assumes that a calf standing sideways and upright in front of cameras is in a suitable pose. However, since such cases rarely occur, not many images were selected. This paper proposes a new depth image-selection method, focusing on whether a calf is sideways, and the back is not bent, regardless of whether the calf is still or walking. First, depth images including only a single calf are extracted. The calf was identified using radio frequency identification (RFID) when its depth image was taken. Then, the calf area was extracted by background subtraction and contour detection with a depth image. Finally, to judge the usable depth images, we detected and evaluated the calf’s posture, such as the angle of the calf to the camera and the slope of the dorsal line. We used the mean absolute percentage error (MAPE) to assess the efficiency of our method. As two times the number of depth images were extracted, our method achieved an MAPE of 12.45%, while the existing method achieved an MAPE of 13.87%. From this result, we have confirmed that our method makes body weight estimation more accurate.

Research on Radio Frequency Identification Technology

2013 ◽  
Vol 299 ◽  
pp. 152-155 ◽  
Author(s):  
Xu Ling Hu
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Security Management ◽  
Logistics Management ◽  
Automatic Identification ◽  
Rfid Technology ◽  
Transportation Management ◽  
Animal Management ◽  
Frequency Identification ◽  
Production Automation

Radio frequency identification (RFID) is an automatic identification technology, is characterized by its greatest non-contact identification. In recent years, RFID technology is widely used in transportation management, logistics management, production automation, security access checking, warehousing management, security management, animal management, and other fields. Apply RFID technology to manage applications for research is important.

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