scholarly journals Production Losses From an Endemic Animal Disease: Porcine Reproductive and Respiratory Syndrome (PRRS) in Selected Midwest US Sow Farms

Author(s):  
Pablo Valdes-Donoso ◽  
Julio Alvarez ◽  
Lovell S. Jarvis ◽  
Robert B. Morrison ◽  
Andres M. Perez
2021 ◽  
Vol 2 (2) ◽  
pp. 83-90
Author(s):  
Dem Vi Sara ◽  
MDD Maharani ◽  
Hafiza Farwa Amin ◽  
Yaya Sudarya Triana

Climate change could lead to an increase in diseases in plants and animals. Plant pathogens have caused devastating production losses, such as in tropical countries. The development of algorithms that match the accuracy of plant and animal disease detection in predicting the toxicity of substances has continued through a massive database. Data and information from 10,000 substances from more than 800,000 animal tests have been carried out to generate the algorithms. Plant and animal disease detection using artificial intelligent in the modern ecological era is important and needed. Diseases in animals are still found in several Ruminant-Slaughterhouses. The purpose of the study is to identify the leverage attributes for using of Artificial Intelligent (AI) in detecting plant pests and animal diseases. The use of Multidimensional Scaling (MDS) produces a leverage attribute for the use of AI in detecting plant pests and animal diseases. The results showed that leverage attributes found were: Prediction of the presence of proteins structures produced by pathogens with a Root Mean Square (RMS) value of 4.5123; and Plant and Animal Disease Data will be opened with an RMS value of 4.2555. The findings of this study in the real world are to produce the development of smart agricultural applications in detecting plant pests and animal diseases as an early warning system. In addition, the application is also useful for eco-tourism managers who have a natural close relationship with plants and animals, so that ecological security in the modern ecological era, can be better maintained.


Author(s):  
Ian Convery ◽  
Maggie Mort ◽  
Josephine Baxter ◽  
Cathy Bailey
Keyword(s):  

2020 ◽  
Vol 2 (11) ◽  
pp. 71-73
Author(s):  
M. U. USUPOV ◽  

The article is devoted to the state of the economy of the subject of the agricultural sector – the Toktogul region of Kyrgyzstan, as well as the formation of a land division, which is impossible without an influx of investments and ensuring the availability of monetary resources for agricultural producers. In our time, innovation is becoming the main means of increasing the benefits of economic entities by better meeting market demand and reducing production losses compared to competitors. Despite repeated attempts by the country to create a system of lending to agricultural companies, only a small percentage of them use credit resources. Various state aid schemes support a competitive environment in the money markets and guarantee relatively equal access to them for financial institutions and agricultural enterprises.


2020 ◽  
Vol 15 ◽  
Author(s):  
Shuwen Zhang ◽  
Qiang Su ◽  
Qin Chen

Abstract: Major animal diseases pose a great threat to animal husbandry and human beings. With the deepening of globalization and the abundance of data resources, the prediction and analysis of animal diseases by using big data are becoming more and more important. The focus of machine learning is to make computers learn how to learn from data and use the learned experience to analyze and predict. Firstly, this paper introduces the animal epidemic situation and machine learning. Then it briefly introduces the application of machine learning in animal disease analysis and prediction. Machine learning is mainly divided into supervised learning and unsupervised learning. Supervised learning includes support vector machines, naive bayes, decision trees, random forests, logistic regression, artificial neural networks, deep learning, and AdaBoost. Unsupervised learning has maximum expectation algorithm, principal component analysis hierarchical clustering algorithm and maxent. Through the discussion of this paper, people have a clearer concept of machine learning and understand its application prospect in animal diseases.


BMJ ◽  
1976 ◽  
Vol 1 (6008) ◽  
pp. 521-522
Author(s):  
J R Wilkie
Keyword(s):  

2021 ◽  
Vol 9 (6) ◽  
pp. 1234
Author(s):  
Dejan Vidanović ◽  
Bojana Tešović ◽  
Milanko Šekler ◽  
Zoran Debeljak ◽  
Nikola Vasković ◽  
...  

Lumpy skin disease (LSD) is an important animal disease with significant health and economic impacts. It is considered a notifiable disease by the OIE. Attenuated strains of LSDV have been successfully used as vaccines (LAV) but can also produce mild or systemic reactions. Vaccination campaigns using LAVs are therefore only viable if accompanying DIVA assays are available. Two DIVA qPCR assays able to distinguish Neethling-based LAVs and wild-type LSDV were developed. Upon validation, both assays were shown to have high sensitivity and specificity with a diagnostic performance comparable to other published DIVA assays. This confirmed their potential as reliable tools to confirm infection in animals during vaccination campaigns based on Neethling vaccine strains.


Biomolecules ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 831
Author(s):  
Patrycja Burzyńska ◽  
Łukasz F. Sobala ◽  
Krzysztof Mikołajczyk ◽  
Marlena Jodłowska ◽  
Ewa Jaśkiewicz

Carbohydrates have long been known to mediate intracellular interactions, whether within one organism or between different organisms. Sialic acids (Sias) are carbohydrates that usually occupy the terminal positions in longer carbohydrate chains, which makes them common recognition targets mediating these interactions. In this review, we summarize the knowledge about animal disease-causing agents such as viruses, bacteria and protozoa (including the malaria parasite Plasmodium falciparum) in which Sias play a role in infection biology. While Sias may promote binding of, e.g., influenza viruses and SV40, they act as decoys for betacoronaviruses. The presence of two common forms of Sias, Neu5Ac and Neu5Gc, is species-specific, and in humans, the enzyme converting Neu5Ac to Neu5Gc (CMAH, CMP-Neu5Ac hydroxylase) is lost, most likely due to adaptation to pathogen regimes; we discuss the research about the influence of malaria on this trait. In addition, we present data suggesting the CMAH gene was probably present in the ancestor of animals, shedding light on its glycobiology. We predict that a better understanding of the role of Sias in disease vectors would lead to more effective clinical interventions.


Author(s):  
Viktor P. Kuznetsov ◽  
Igor E. Mizikovsky ◽  
Ekaterina P. Garina ◽  
Elena V. Romanovskaya ◽  
Natalia S. Andryashina

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