scholarly journals Forecasting beef production and quality using large-scale integrated data from Brazil

2020 ◽  
Vol 98 (4) ◽  
Author(s):  
Vera Cardoso Ferreira Aiken ◽  
Arthur Francisco Araújo Fernandes ◽  
Tiago Luciano Passafaro ◽  
Juliano Sabella Acedo ◽  
Fábio Guerra Dias ◽  
...  
Keyword(s):  
Linear Regression ◽  
Beef Cattle ◽  
Large Scale ◽  
National Level ◽  
Parameter Tuning ◽  
Absolute Error ◽  
Meat Production ◽  
Beef Production ◽  
Production Chain ◽  
Testing Set

Abstract With agriculture rapidly becoming a data-driven field, it is imperative to extract useful information from large data collections to optimize the production systems. We compared the efficacy of regression (linear regression or generalized linear regression [GLR] for continuous or categorical outcomes, respectively), random forests (RF) and multilayer neural networks (NN) to predict beef carcass weight (CW), age when finished (AS), fat deposition (FD), and carcass quality (CQ). The data analyzed contained information on over 4 million beef cattle from 5,204 farms, corresponding to 4.3% of Brazil’s national production between 2014 and 2016. Explanatory variables were integrated from different data sources and encompassed animal traits, participation in a technical advising program, nutritional products sold to farms, economic variables related to beef production, month when finished, soil fertility, and climate in the location in which animals were raised. The training set was composed of information collected in 2014 and 2015, while the testing set had information recorded in 2016. After parameter tuning for each algorithm, models were used to predict the testing set. The best model to predict CW and AS was RF (CW: predicted root mean square error = 0.65, R2 = 0.61, and mean absolute error = 0.49; AS: accuracy = 28.7%, Cohen’s kappa coefficient [Kappa] = 0.08). While the best approach for FD and CQ was GLR (accuracy = 45.7%, Kappa = 0.05, and accuracy = 58.7%, Kappa = 0.09, respectively). Across all models, there was a tendency for better performance with RF and regression and worse with NN. Animal category, nutritional plan, cattle sales price, participation in a technical advising program, and climate and soil in which animals were raised were deemed important for prediction of meat production and quality with regression and RF. The development of strategies for prediction of livestock production using real-world large-scale data will be core to projecting future trends and optimizing the allocation of resources at all levels of the production chain, rendering animal production more sustainable. Despite beef cattle production being a complex system, this analysis shows that by integrating different sources of data it is possible to forecast meat production and quality at the national level with moderate-high levels of accuracy.

scholarly journals Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain

2016 ◽  
Vol 82 (8) ◽  
pp. 2433-2443 ◽  
Author(s):  
Xiang Yang ◽  
Noelle R. Noyes ◽  
Enrique Doster ◽  
Jennifer N. Martin ◽  
Lyndsey M. Linke ◽  
...  
Keyword(s):  
Pathogenic Bacteria ◽  
Shotgun Sequencing ◽  
Meat Production ◽  
Global Public Health ◽  
Beef Production ◽  
Sequencing Technology ◽  
Production Chain ◽  
Shotgun Metagenomics ◽  
Content Type ◽  
Processing Steps

ABSTRACTFoodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads forSalmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus,Clostridiumspp. (C. botulinumandC. perfringens), andCampylobacterspp. (C. jejuni,C. coli, andC. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts forS. enterica,E. coli, andC. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.

scholarly journals ANALISIS KEUNTUNGAN FINANSIAL USAHA PENGGEMUKAN SAPI POTONG DI KABUPATEN BOJONEGORO

2017 ◽  
Vol 11 (2) ◽  
pp. 207
Author(s):  
Retna D Lestari ◽  
Lukman M Baga ◽  
Rita Nurmalina
Keyword(s):  
Beef Cattle ◽  
Large Scale ◽  
Net Present Value ◽  
Meat Production ◽  
Cattle Farm ◽  
Average Value ◽  
Financial Benefits ◽  
The Government ◽  
Increasing Demand ◽  
Break Even Point

Cattle  farm  agribusiness  in  Indonesia  is  still  a  sector  that  needs  to  be developed,  given  the  increasing  demand  for  meat,  but  has  not  met  from  domestic meat  production.  One  of  the  efforts  to  achieve  stability  availability  of  beef  that  is through  an  increase  in  beef  cattle  fattening  which  have  long-term  prospects.  This study  aims  to  identify  and  analyze  the  financial  benefits  fattening  beef  cattle  in Bojonegoro  which  is  one  of  the  central  areas  of  the  cow  kind  Peranakan  Ongole (PO)  in  the  province  of  East  Java.  Data  were  analyzed  quantitatively  by  using indicators  of  profitability  and  feasibility  ie  B  /  C  Ratio,  Break  Even  Point,  Net Present Value, Internal Rate of Return, and Payback Period. The research location in  the  village  Napis,  District  Tambakrejo  with  30  respondents  breeders  who  do fattening for 4 months. The results showed the average value of B / C ratio of 1.23, NPV of USD 481 110, 59, IRR 11.30%, and PBP for 2 years and 9 months. Based on the research results can be suggested to the Government of Bojonegoro in order to provide  guidance  and  directs  farmers  to  conduct  fattening  cattle  given  the  small number of farmers who cultivate the cow on a large scale.

scholarly journals Cell-Based Meat and Firms’ Environmental Strategies: New Rationales as per Available Literature

2020 ◽  
Vol 12 (22) ◽  
pp. 9418
Author(s):  
Germano Glufke Reis ◽  
Marina Sucha Heidemann ◽  
Katherine Helena Oliveira de Matos ◽  
Carla Forte Maiolino Molento
Keyword(s):  
Value Chain ◽  
Large Scale ◽  
Animal Ethics ◽  
Consumer Attitudes ◽  
Environmental Benefits ◽  
Meat Production ◽  
Review Of The Literature ◽  
Production Chain ◽  
Alternative Protein ◽  
Environmental Strategies

Higher demand for meat production and limited inputs, as well as environmental and animal ethics issues, are bringing alternative protein sources to the market, such as cell-based meat (CBM), i.e., meat produced through cell culturing, without involving animal raising and killing. Although the potential social and environmental benefits of the technology have been recently addressed in the blossoming CBM literature, little has been discussed about the possible implications for the environmental strategies of firms that are entering the new cell-based production chain. Thus, drawing on the theoretical framework of competitive environmental strategies and a systematic review of the literature, we discuss prospects for cell-based meat regarding the possible adoption of environmental strategies by firms that are entering the CBM chain. The technology may be considered a potential means for mitigating most of the environmental impacts of large-scale meat production, e.g., extensive land use and greenhouse gas emissions. We discuss how such benefits and consumer attitudes towards cultivated meat could encourage the adoption of environmental strategies by firms, and the roles that value chain firms are likely to play in those strategies in the future.

scholarly journals Isolation and Characterization of Clostridium difficile Associated with Beef Cattle and Commercially Produced Ground Beef

2013 ◽  
Vol 76 (2) ◽  
pp. 256-264 ◽  
Author(s):  
NORASAK KALCHAYANAND ◽  
TERRANCE M. ARTHUR ◽  
JOSEPH M. BOSILEVAC ◽  
DAYNA M. BRICHTA-HARHAY ◽  
STEVEN D. SHACKELFORD ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Beef Cattle ◽  
Meat Products ◽  
Ground Beef ◽  
The United States ◽  
Ground Meat ◽  
Beef Production ◽  
Production Chain ◽  
Isolation And Characterization ◽  
Beef Products

The incidence of Clostridium difficile infection has recently increased in North American and European countries. This pathogen has been isolated from retail pork, turkey, and beef products and reported associated with human illness. This increase in infections has been attributed to the emergence of a toxigenic strain designated North America pulsed-field gel electrophoresis type 1 (NAP1). The NAP1 strain has been isolated from calves as well as ground meat products, leading to speculation of illness from consumption of contaminated meat products. However, information on C. difficile associated with beef cattle during processing and commercially produced ground beef is limited. To address this data gap, samples from various steps during beef production were collected. Samples from hides (n = 525), preevisceration carcasses (n = 475), postintervention carcasses (n = 471), and 956 commercial ground beef samples were collected from across the United States. The prevalence of C. difficile spores on hides was 3.2%. C. difficile spores were not detected on preevisceration and postintervention carcasses or in commercially produced ground beef. Phenotypic and genetic characterizations were carried out for all 18 isolates collected from hide samples. Twenty-two percent of the isolates were nontoxigenic strains, while 78% of the isolates were toxigenic. Toxinotyping and PCR ribotyping patterns revealed that 6 and 33% of the isolates were identified as NAP1 and NAP7 strains, respectively. This article evidences that the prevalence of C. difficile, specifically pathogenic strains, in the U.S. beef production chain is low.

scholarly journals Rabbit meat sector value chain

2017 ◽  
Vol 25 (1) ◽  
pp. 95 ◽  
Author(s):  
A. Baviera-Puig ◽  
J. Buitrago-Vera ◽  
C. Escriba-Perez ◽  
L. Montero-Vicente
Keyword(s):  
Value Chain ◽  
Large Scale ◽  
Economies Of Scale ◽  
Distribution Channel ◽  
Added Value ◽  
Meat Production ◽  
Chain Model ◽  
Production Chain ◽  
Self Service ◽  
Rabbit Meat

<p>The aim of this research was to study the cuniculture industry in Spain, according to the Food Value Chain model, and analyse what its main operators are. Four components were identified in the rabbit meat production chain: input suppliers, producers, abattoirs and cutting plants and distribution. Distribution can follow 2 paths, the traditional channel and the modern or large-scale distribution channel. Rabbit feed, which represents the main input for producers, is a minority product, especially when compared to feeds formulated for other livestock species, as its manufacture calls for specialist companies. Rabbit production is linked to the rural environment and constitutes a significant economic option, not only for farms but also for the industry around it, such as feed producers and distributors, technicians, slaughterhouses or leather processors, among others. Rabbit farms are generally independent and not usually integrated, as found in other types of livestock. Slaughterhouses currently represent one of the main axes of the rabbit meat production chain and are either focused on traditional or large-scale distribution. The main strategic changes are apparent in slaughterhouses focused on large-scale distribution by seeking cooperative ways of working, using slaughterhouse groupings and vertical integration processes. This way, they manage to adjust margins by working with economies of scale and, ultimately, lower prices. Slaughterhouses whose strategies are based on traditional distribution may achieve higher margins than those focusing their efforts on large-scale distribution, but their growth is limited. In traditional retail premises, the majority of sales consist of whole carcasses in bulk, which are prepared and quartered as per consumer tastes. Large-scale retail distribution outlets sell both cut produce from the meat counters located in their own premises and pre-packaged products, more suited to self-service formulae. Brand presence is minimal, as is that of processed or semiprocessed products. This current situation requires support from the entire sector in order to provide rabbit<br />meat with new features better adapted to consumers’ needs, above and beyond price and with greater added value.</p>

HOME VISITS DURING THE FIRST MONTH OF DELIVERY FOR RECENTLY DELIVERED WOMEN IN UTTAR PRADESH, INDIA

2020 ◽  
Vol 6 (5) ◽  
pp. 1183-1189
Author(s):  
Dr. Tridibesh Tripathy ◽  
Dr. Umakant Prusty ◽  
Dr. Chintamani Nayak ◽  
Dr. Rakesh Dwivedi ◽  
Dr. Mohini Gautam
Keyword(s):  
Large Scale ◽  
National Level ◽  
Uttar Pradesh ◽  
Life Time ◽  
Structured Interview ◽  
The Other ◽  
Registration System ◽  
Action Group ◽  
Current Article ◽  
The Impact

The current article of Uttar Pradesh (UP) is about the ASHAs who are the daughters-in-law of a family that resides in the same community that they serve as the grassroots health worker since 2005 when the NRHM was introduced in the Empowered Action Group (EAG) states. UP is one such Empowered Action Group (EAG) state. The current study explores the actual responses of Recently Delivered Women (RDW) on their visits during the first month of their recent delivery. From the catchment area of each of the 250 ASHAs, two RDWs were selected who had a child in the age group of 3 to 6 months during the survey. The response profiles of the RDWs on the post- delivery first month visits are dwelled upon to evolve a picture representing the entire state of UP. The relevance of the study assumes significance as detailed data on the modalities of postnatal visits are available but not exclusively for the first month period of their recent delivery. The details of the post-delivery first month period related visits are not available even in large scale surveys like National Family Health Survey 4 done in 2015-16. The current study gives an insight in to these visits with a five-point approach i.e. type of personnel doing the visit, frequency of the visits, visits done in a particular week from among those four weeks separately for the three visits separately. The current study is basically regarding the summary of this Penta approach for the post- delivery one-month period.     The first month period after each delivery deals with 70% of the time of the postnatal period & the entire neonatal period. Therefore, it does impact the Maternal Mortality Rate & Ratio (MMR) & the Neonatal Mortality Rates (NMR) in India and especially in UP through the unsafe Maternal & Neonatal practices in the first month period after delivery. The current MM Rate of UP is 20.1 & MM Ratio is 216 whereas the MM ratio is 122 in India (SRS, 2019). The Sample Registration System (SRS) report also mentions that the Life Time Risk (LTR) of a woman in pregnancy is 0.7% which is the highest in the nation (SRS, 2019). This means it is very risky to give birth in UP in comparison to other regions in the country (SRS, 2019). This risk is at the peak in the first month period after each delivery. Similarly, the current NMR in India is 23 per 1000 livebirths (UNIGME,2018). As NMR data is not available separately for states, the national level data also hold good for the states and that’s how for the state of UP as well. These mortalities are the impact indicators and such indicators can be reduced through long drawn processes that includes effective and timely visits to RDWs especially in the first month period after delivery. This would help in making their post-natal & neonatal stage safe. This is the area of post-delivery first month visit profile detailing that the current article helps in popping out in relation to the recent delivery of the respondents.   A total of four districts of Uttar Pradesh were selected purposively for the study and the data collection was conducted in the villages of the respective districts with the help of a pre-tested structured interview schedule with both close-ended and open-ended questions.  The current article deals with five close ended questions with options, two for the type of personnel & frequency while the other three are for each of the three visits in the first month after the recent delivery of respondents. In addition, in-depth interviews were also conducted amongst the RDWs and a total 500 respondents had participated in the study.   Among the districts related to this article, the results showed that ASHA was the type of personnel who did the majority of visits in all the four districts. On the other hand, 25-40% of RDWs in all the 4 districts replied that they did not receive any visit within the first month of their recent delivery. Regarding frequency, most of the RDWs in all the 4 districts received 1-2 times visits by ASHAs.   Regarding the first visit, it was found that the ASHAs of Barabanki and Gonda visited less percentage of RDWs in the first week after delivery. Similarly, the second visit revealed that about 1.2% RDWs in Banda district could not recall about the visit. Further on the second visit, the RDWs responded that most of them in 3 districts except Gonda district did receive the second postnatal visit in 7-15 days after their recent delivery. Less than half of RDWs in Barabanki district & just more than half of RDWs in Gonda district received the third visit in 15-21 days period after delivery. For the same period, the majority of RDWs in the rest two districts responded that they had been entertained through a home visit.

0552 - Tracing microbial contamination sources in the meat production chain

2018 ◽  
Author(s):  
Benjamin Zwirzitz ◽  
Stefanie Urimare Wetzels ◽  
Beate Pinior ◽  
Evelyne Mann
Keyword(s):  
Microbial Contamination ◽  
Meat Production ◽  
Production Chain ◽  
Contamination Sources

Benchmark of Simplified Time-Dependent Density Functional Theory for UV-Vis Spectral Properties of Porphyrinoids

2019 ◽  
Author(s):  
Kamal Batra ◽  
Stefan Zahn ◽  
Thomas Heine
Keyword(s):  
Density Functional Theory ◽  
Density Functional ◽  
Large Scale ◽  
Absolute Error ◽  
Time Dependent ◽  
Basis Set ◽  
Basis Sets ◽  
Functional Theory ◽  
Framework Materials ◽  
Dependent Density

<p>We thoroughly benchmark time-dependent density- functional theory for the predictive calculation of UV/Vis spectra of porphyrin derivatives. With the aim to provide an approach that is computationally feasible for large-scale applications such as biological systems or molecular framework materials, albeit performing with high accuracy for the Q-bands, we compare the results given by various computational protocols, including basis sets, density-functionals (including gradient corrected local functionals, hybrids, double hybrids and range-separated functionals), and various variants of time-dependent density-functional theory, including the simplified Tamm-Dancoff approximation. An excellent choice for these calculations is the range-separated functional CAM-B3LYP in combination with the simplified Tamm-Dancoff approximation and a basis set of double-ζ quality def2-SVP (mean absolute error [MAE] of ~0.05 eV). This is not surpassed by more expensive approaches, not even by double hybrid functionals, and solely systematic excitation energy scaling slightly improves the results (MAE ~0.04 eV). </p>

scholarly journals Analysis of 220 Years of Floodplain Population Dynamics in the US at Different Spatial Scales

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 141
Author(s):  
Firoza Akhter ◽  
Maurizio Mazzoleni ◽  
Luigia Brandimarte
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Spatial Scales ◽  
National Level ◽  
State Level ◽  
Economic Activities ◽  
Protection Measures ◽  
Management Planning ◽  
The Us ◽  
Over Time

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.

scholarly journals Developing Equations for Converting Digestible Energy to Metabolizable Energy for Korean Hanwoo Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1696
Author(s):  
Ridha Ibidhi ◽  
Rajaraman Bharanidharan ◽  
Jong-Geun Kim ◽  
Woo-Hyeong Hong ◽  
In-Sik Nam ◽  
...  
Keyword(s):  
Linear Regression ◽  
Beef Cattle ◽  
Strong Relationship ◽  
Dietary Factors ◽  
Metabolizable Energy ◽  
Coefficient Of Determination ◽  
Simple Linear Regression ◽  
Male And Female ◽  
Digestible Energy ◽  
Wide Range

This study was performed to update and generate prediction equations for converting digestible energy (DE) to metabolizable energy (ME) for Korean Hanwoo beef cattle, taking into consideration the gender (male and female) and body weights (BW above and below 350 kg) of the animals. The data consisted of 141 measurements from respiratory chambers with a wide range of diets and energy intake levels. A simple linear regression of the overall unadjusted data suggested a strong relationship between the DE and ME (Mcal/kg DM): ME = 0.8722 × DE + 0.0016 (coefficient of determination (R2) = 0.946, root mean square error (RMSE) = 0.107, p < 0.001 for intercept and slope). Mixed-model regression analyses to adjust for the effects of the experiment from which the data were obtained similarly showed a strong linear relationship between the DE and ME (Mcal/kg of DM): ME = 0.9215 × DE − 0.1434 (R2 = 0.999, RMSE = 0.004, p < 0.001 for the intercept and slope). The DE was strongly related to the ME for both genders: ME = 0.8621 × DE + 0.0808 (R2 = 0.9600, RMSE = 0.083, p < 0.001 for the intercept and slope) and ME = 0.7785 × DE + 0.1546 (R2 = 0.971, RMSE = 0.070, p < 0.001 for the intercept and slope) for male and female Hanwoo cattle, respectively. By BW, the simple linear regression similarly showed a strong relationship between the DE and ME for Hanwoo above and below 350 kg BW: ME = 0.9833 × DE − 0.2760 (R2 = 0.991, RMSE = 0.055, p < 0.001 for the intercept and slope) and ME = 0.72975 × DE + 0.38744 (R2 = 0.913, RMSE = 0.100, p < 0.001 for the intercept and slope), respectively. A multiple regression using the DE and dietary factors as independent variables did not improve the accuracy of the ME prediction (ME = 1.149 × DE − 0.045 × crude protein + 0.011 × neutral detergent fibre − 0.027 × acid detergent fibre + 0.683).

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