117 Nutrition Modelling: What Can the Pet Field Learn (or Steal) from Recent Directions in Other Species?

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 62-63
Author(s):  
Jennifer L Ellis
Keyword(s):  
Egg Production ◽  
Nutrient Dynamics ◽  
Data Extraction ◽  
Animal Production ◽  
Sensor Data ◽  
Biological Knowledge ◽  
Mechanistic Models ◽  
Management Scenarios ◽  
Metabolite Level ◽  
Causal Pathway

Abstract Nutrition modelling has been the cornerstone of feed formulation and diet optimization in animal production systems for decades. Since the 1970s and 1980s, mechanistic models of nutrient digestion, absorption, metabolism, growth and milk/egg production have been developed and implemented to (1) amass our cumulative biological knowledge and develop theories of regulation, (2) identify knowledge gaps, and (3) propose means to manipulate nutrient dynamics in the animal. At the nutrient and metabolite level, many commonalities exist and parallels found between species. In fact, several second generation models originate from other species or research fields, and many current/existing models may be advanced by examination and consideration of models developed in other species. Many such mathematical models are implemented in practice as ‘decision support systems’ or ‘opportunity analysis tools’, in order to examine a variety of (feeding or management) scenarios for their potential outcomes, with the goal of providing targeted nutrition, improving performance, reducing cost and minimizing environmental impact. More recently, partnering artificial intelligence/machine learning modelling methodologies with newly available big data streams has ushered in a new era of possibilities for data extraction and modelling in animal systems. The niche for this type of modelling in animal production appears to be (1) pattern recognition (e.g. disease detection, activity) and (2) strong predictive/forecasting abilities (e.g. bodyweight, milk, egg production). There also appears strong potential for these two seemingly divergent modelling approaches to be integrated – for example, in precision feeding systems, or in utilizing the abundance of sensor data to better drive or develop causal-pathway based mechanistic models. This talk will broadly review trends and advances in agriculture animal species modelling, and suggest what may be borrowed, stolen or serve as inspiration to advance nutrition models in companion species.

scholarly journals Time Optimization for Lossy Decompression of the LISA Sensor Data on LAPAN A3 Satellite Using a Grouping Method of HUFFMAN Code Bit Number

2018 ◽  
Vol 16 (1) ◽  
pp. 23
Author(s):  
Suhermanto M.T
Keyword(s):  
Real Time ◽  
Performance Test ◽  
Data Extraction ◽  
Extraction Process ◽  
Lossy Compression ◽  
Extraction Time ◽  
Sensor Data ◽  
Multispectral Data ◽  
Grouping Method ◽  
The Fourier Transform

The LAPAN-A3 satellite provides compressed multispectral data from LISA sensor using real-time lossy compression. The compression of the multispectral data of radiometric resolution 12bit/pixel is built from the Fourier transform and the use of Huffman decoder 514 binary length code. A problem arised in the data extraction process, that decompression performance is very slow because the search method of code value in Hufman table was done sequentially from one bit to the next bit in one block of data along 4000 pixels. The data extraction time for one scene in 12 minutes acquisition duration (one full path) takes up to 20 hours. This paper proposes a method of improving the LISA real-time lossy data decompression algorithm using the grouping method of bit code on the Huffman decoding algorithm and using pointer for reading data in the buffer memory. Using this method, the searching process of bit code for all characters in the Huffman decoder algorithm is done regularly, so the search processing time is significantly reduced. The performance test used 6 data samples. The result showed that extraction time has an average of 14 times faster. The lossy compression ratio is still in accordance with the design specification of LISA sensor that is less than 4 times and the appearance of the special character is very small i.e. less than 0.5%.

scholarly journals The Influence of Housing for Laying Hens on the Economics of Egg Production

2020 ◽  
Vol 8 (6) ◽  
Author(s):  
Silvia Ondrašovičová ◽  
Katarína Veszelits Laktičová ◽  
Mária Vargová ◽  
František Zigo
Keyword(s):  
Food Safety ◽  
Organic Farming ◽  
Egg Production ◽  
Laying Hens ◽  
Animal Production ◽  
Healthy Food ◽  
Free Range ◽  
Environmental Consequences ◽  
Stable Production ◽  
Industry Sustainability

The poultry sector plays an important role in animal production in terms of maintaining a stable production of healthy food for the population. With regard to the egg industry, sustainability refers to the treatment of laying hens and especially the systems used for hen housing. The conditions of welfare and housing of laying hens in the production of table eggs are currently of interest to most egg sellers as well as consumers as they directly affect the economy of their production and their price. At present, consumers have a choice of four types of eggs on the shelves. They can come from the cage, litter, free-range or organic farming. Each farm has well-defined rules that it must follow. Customers are increasingly interested in where and under what circumstances are produced the eggs which they bring home from the store. In addition to price, customers look for a story behind the package and make their decisions accordingly. Although recognizing that issues such as environmental consequences, food safety, and humane treatment of hens are also important, this article focuses on the relationships between hen housing and economy and market eggs production.

scholarly journals The importance of capital and labour in animal production

1971 ◽  
Vol 43 (3) ◽  
pp. 159-166
Author(s):  
N. Westermarck
Keyword(s):  
Capital Investment ◽  
Egg Production ◽  
Animal Husbandry ◽  
Animal Production ◽  
Production Factor ◽  
Family Farms ◽  
Pork Production ◽  
Labour Input ◽  
Modern Family ◽  
Crop Husbandry

Technical development in animal production, as in agricultural production in general has a twofold function. The first is to substitute capital for human labour, and the second is to gain a higher yield per animal unit. Especially in animal production carried on with hired labour, the production factor capital is substituting the production factor labour at an accelerated rate. In animal husbandry the capital investment in relation to the labour input on modern family farms is, on an average, less than the capital investment in crop husbandry. At the same time it appears also that on the smaller farms the compared values lie closer to each other, while increasing size of farms leads to a much greater increase of capital investment in crop husbandry than in animal husbandry. The need of capital occurs for two different purposes: for investments and circulating capital. The need of circulating capital in relation to the amount of sales (gross return) is 21/2 times greater in milk and beef production than in pork or egg production. In relation to the need of investment capital the demand for circulating capital is particularly great in beef and pork production. The high demand for circulating capital in pork production in relation to the labour input is connected with, among others, the continuous need of large replacements. At a given labour input the capital investment in relation to sales is considerably higher in milk production than in pork production, while egg production occupies an intermediate position.

scholarly journals THE EFFICACY OF PAPAYA LEAF EXTRACT INCLUSION IN DRINKING WATER AS AN IMPROVING OF LAYER QUAIL PRODUCTION

2017 ◽  
Vol 3 (1) ◽  
pp. 31
Author(s):  
Asri Kusbiyantari ◽  
Dede Kardaya ◽  
Deden Sudrajat
Keyword(s):  
Drinking Water ◽  
Egg Production ◽  
Pathogenic Bacteria ◽  
Leaf Extract ◽  
Production Efficiency ◽  
Bacterial Resistance ◽  
Antibacterial Properties ◽  
Animal Production ◽  
Egg Mass ◽  
Feed Conversion

Bacterial resistance to antibiotic has made the reduction in the use of antibiotic a concern in animal production.  The restriction of antibiotic application in animal production can be achieved if the antimicrobial strategy is available.  Papaya leaf extract has some antibacterial properties that make it is potential to be used as a substitute for commercial antibiotic.  This study was aimed at assessing the efficacy and potential of papaya leaf extract inclusion in drinking water in controlling pathogenic bacteria and improving the production efficiency and feed conversion ratio (FCR) of layer quails.  The study was conducted from 24 August to 20 September 2016 at the poultry farm of Department of Animal Husbandry, Djuanda University, Bogor.  One-hundred layer quails were allocated into 4 treatments and 3 replicates in a completely randomized design.  The treatments consisted of five levels of papaya leaf extract inclusions in drinking water , namely drinking water + commercial antibiotic of 0.5 g/liter water (R1), drinking water + papaya leaf extract of 10 ml/liter water (R2), drinking water + papaya leaf extract of 20 ml/liter water (R3), and drinking water + papaya leaf extract of 30 ml/liter water (R4).  Data were subjected to an analysis of variance and a Duncan test.  Results showed that the inclusion of papaya leaf extract in drinking water gave significant effects on egg mass, egg production efficiency, FCR, egg quality index, and egg shell thickness but not on feed intake, egg weight, and mortality rate.  It was concluded that papaya leaf extract produced by a boiling method could be used as a substitute for synthetic antibiotic.  Key words: Papaya leaf extract, production efficiency, feed conversion, layer quail.  

The road towards data integration in human genomics: players, steps and interactions

2020 ◽  
Author(s):  
Anna Bernasconi ◽  
Arif Canakoglu ◽  
Marco Masseroli ◽  
Stefano Ceri
Keyword(s):  
Data Integration ◽  
Data Extraction ◽  
Genomic Data ◽  
Heterogeneous Data ◽  
Biological Knowledge ◽  
Multiple Perspectives ◽  
The Road ◽  
Effective Combination ◽  
Experimental Values ◽  
Meaningful Relationships

Abstract Thousands of new experimental datasets are becoming available every day; in many cases, they are produced within the scope of large cooperative efforts, involving a variety of laboratories spread all over the world, and typically open for public use. Although the potential collective amount of available information is huge, the effective combination of such public sources is hindered by data heterogeneity, as the datasets exhibit a wide variety of notations and formats, concerning both experimental values and metadata. Thus, data integration is becoming a fundamental activity, to be performed prior to data analysis and biological knowledge discovery, consisting of subsequent steps of data extraction, normalization, matching and enrichment; once applied to heterogeneous data sources, it builds multiple perspectives over the genome, leading to the identification of meaningful relationships that could not be perceived by using incompatible data formats. In this paper, we first describe a technological pipeline from data production to data integration; we then propose a taxonomy of genomic data players (based on the distinction between contributors, repository hosts, consortia, integrators and consumers) and apply the taxonomy to describe about 30 important players in genomic data management. We specifically focus on the integrator players and analyse the issues in solving the genomic data integration challenges, as well as evaluate the computational environments that they provide to follow up data integration by means of visualization and analysis tools.

scholarly journals Elevator Fault Detection Using Profile Extraction and Deep Autoencoder Feature Extraction for Acceleration and Magnetic Signals

2019 ◽  
Vol 9 (15) ◽  
pp. 2990 ◽  
Author(s):  
Krishna Mohan Mishra ◽  
Kalevi Huhtala
Keyword(s):  
Feature Extraction ◽  
Random Forest ◽  
Fault Detection ◽  
Time Series Data ◽  
Data Extraction ◽  
False Positives ◽  
Sensor Data ◽  
Series Data ◽  
False Alarms ◽  
Maintenance Systems

In this paper, we propose a new algorithm for data extraction from time-series data, and furthermore automatic calculation of highly informative deep features to be used in fault detection. In data extraction, elevator start and stop events are extracted from sensor data including both acceleration and magnetic signals. In addition, a generic deep autoencoder model is also developed for automated feature extraction from the extracted profiles. After this, extracted deep features are classified with random forest algorithm for fault detection. Sensor data are labelled as healthy and faulty based on the maintenance actions recorded. The remaining healthy data are used for validation of the model to prove its efficacy in terms of avoiding false positives. We have achieved above 90% accuracy in fault detection along with avoiding false positives based on new extracted deep features, which outperforms results using existing features. Existing features are also classified with random forest to compare results. Our developed algorithm provides better results due to the new deep features extracted from the dataset when compared to existing features. This research will help various predictive maintenance systems to detect false alarms, which will in turn reduce unnecessary visits of service technicians to installation sites.

Nutrient Dynamics Buoy (Ndb) Sensor Data and Calibration Report

2020 ◽  
pp. 1-10
Author(s):  
Alex Lisowsky ◽  
Keyword(s):  
Water Surface ◽  
Nutrient Dynamics ◽  
Sensor Data ◽  
Nitrate Sensor ◽  
Phosphate Sensor

The Nutrient Dynamics Buoy (NDB) is currently based on a multi-parameter sonde with 7 sensors and includes an integrated Nitrate Sensor and a Phosphate sensor. It also includes a reference PAR1 sensor mounted at the water surface as well as a submersible PAR1 sensor that is immersed at 2m below the water surface together with the mult-parameter sonde, Nitrate sensor and Phosphate sensor.

scholarly journals Perception of Animal Welfare in Laying Hens and Willingness-to-Pay of Eggs of Consumers in Santiago, Chile

Proceedings ◽  
2020 ◽  
Vol 73 (1) ◽  
pp. 2
Author(s):  
Natalia Morales ◽  
Cristian Ugaz ◽  
Hernan Cañon-Jones
Keyword(s):  
Willingness To Pay ◽  
Animal Welfare ◽  
Egg Production ◽  
Laying Hens ◽  
Production Systems ◽  
Current Knowledge ◽  
Animal Production ◽  
Current Value ◽  
Main City ◽  
Animal Production Systems

We investigated the current knowledge of animal welfare issues, the perception of current welfare of laying hens, and the willingness-to-pay in consumers in Santiago, the main city and capital of Chile. Most people were well educated in animal welfare concepts, and declared that the welfare of laying hens is very important and should be protected, and were willing to pay between 5% and 10% of current value for eggs produced in welfare-friendly systems. Our results show a clear predisposition for choosing products derived from animal production systems that respect animal welfare, which should be considered for the sustainability of egg production in Chile.

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