Innovative Technology & Practices Transforming India’s Poultry Farming Sector

 

Innovative Technology & Practices Transforming India’s Poultry Farming Sector

*P. Sridevi, J. Violet Beaulah, Geetha Ramesh., Subhadra Ravali KS, Asmitha        S.UshaKumary, T.A. Kannan

 *PhD scholar, Department of Veterinary Anatomy,  Madras Veterinary College, Chennai – 600 007.

 

Abstract

Modern poultry farming technology continues to evolve as the industry seeks to improve efficiency, animal welfare, and sustainability while meeting the growing global demand for poultry products.  The automation has helped to greatly increase operational capacity. the use of computer-based technology in the production of eggs, meat, and feed has produced a large amount of data on all operations. Sexing poultry eggs using modern technology is a valuable practice in the poultry industry, as it allows for the selective hatching of male and female chicks. Gene editing technologies, such as CRISPR-Cas9, have the potential to revolutionize egg sexing in poultry. The blockchain technology holds promise for modern poultry farming, it’s important to note that implementing blockchain solutions requires investment in infrastructure, training, and collaboration among industry stakeholders. The modern technologies not only improves the speed and accuracy of bird disease diagnosis but also enhances our understanding of avian diseases and their transmission, leading to better management and prevention strategies. The Automation, digitalization, and big data are indeed becoming crucial components of the poultry industry, contributing significantly to its value chain

Introduction

A very significant area of the livestock industry is the poultry sector. The increasing changes in people’s lifestyles in general and eating habits in particular will be advantageous for the Indian poultry sector. It makes sense that as commercial farms become more organized and technically sophisticated, their share of the market will increase. Egg production has been increasing significantly, according to government data, going from 95 billion in 2017–18 to 105 billion the following year and 114 billion in 2019–20. Poultry farming has been evolving over the years, and new trends continue to emerge as the industry strives to become more efficient, sustainable, and humane. This industry includes a wide range of output levels breeding farms, hatcheries, feed mills, broiler and layer farms, processing plants. The notable trends in poultry farming as of my last knowledge update in September 2021, and it’s possible that more developments have occurred in recent years. Infrastructure includes various housing types, ranging from thatched sheds to automated, climate-controlled sheds, regular channel watering systems to automatic cups and nipples, automatic egg collection, refrigeration systems, nutraceutical and medicine manufacturing units, vaccine manufacturing units, manufacturing mechanical components to electronic gadgets required for various functions.

Contemporary Poultry Farming Innovations

Automation in modern poultry farming refers to the use of advanced technology and machinery to streamline and optimize various aspects of poultry production. This approach has become increasingly popular in the poultry industry due to its potential to improve efficiency, reduce labor costs, and enhance overall productivity. However, the initial investment in automation systems can be significant, and proper training and maintenance are essential to ensure their effective operation. Additionally, farmers must consider the specific needs and challenges of their operation when implementing automation technologies to ensure they align with their goals and resources.

 Here are some key technologies and practices commonly used in modern poultry farming

Sensors

The  use of sensors to monitor and control environmental conditions by activating appropriate devices

Sensor types used in poultry welfare management are DHT11, DHT22, SHT75, and HX71-VI sensors can all be used to monitor temperature and humidity.

1. Environmental Monitoring:

• Temperature and Humidity: Remote sensors can continuously monitor temperature and humidity levels in poultry houses. Maintaining optimal conditions is crucial for the health and growth of birds.
• Control hygro-thermal parameters (temperature and relative humidity)
• Ventilation: Sensors can detect and control ventilation systems to ensure proper air exchange and reduce the risk of respiratory diseases.
• Lighting: Automated lighting systems can be controlled remotely to simulate natural light patterns, influencing bird behaviour and productivity.

2. Livestock Health and Welfare:

• Infrared Imaging: Infrared cameras can be used to detect variations in temperature, helping identify sick birds early.
• Image Analysis: Cameras and machine learning algorithms can analyze bird behavior and detect signs of stress, disease
• Detection of sick animals: based on the ResNet residual network (accuracy of 93.70 %) to monitor broilers’ behavioural physiology and production

3. Feed and Water Management:

• Automated Feeders and Waterers: Remote sensors can monitor feed and water levels, ensuring that birds have access to essential resources.
• Feed Composition Analysis: Spectroscopy and remote sensing can be used to analyze the nutritional content of feed and adjust it accordingly

4. A Manure Management:

• Nitrogen and ammonia Sensors: Remote sensors can monitor ammonia levels in the poultry house helping manage ventilation and reduce health risks

sensors to a Raspberry Pi to control the water level and other parameters, i.e., temperature, smoke, gas, and food dispensing in a poultry farm.

AL/ML Techniques

Machine learning (ML) research has focused on creating computer algorithms that can create new knowledge or enhance knowledge already possessed. ML models use historical data as input to predict new output values. ML is classified as eithersupervised or unsupervised , with many learning models (i.e., classification, regression, clustering) and learning algorithms (i.e., ANN, SVR, random forest, CNN, GLM). Supervisedlearning algorithms use labelled data in their development for accurate classifications or predictions. Unsupervised learning, on the other hand, uses no pre-assigned labels in unravelling unique patterns in datasets

MLtechniques employed to monitoring:

• The environmental parameters (temperature, humidity, carbon dioxide, and ammonia) include linear regression, fuzzy logic (Lahlouh et al., 2020, neuro-fuzzy and ANN and deep learning
• The estimating the body temperature (heat stress) of broilers include Lasso regression, Fuzzy-GA and generalized sequential pattern.
• The behavioural activities like eating, drinking, preening, and resting, are important as good welfare promotes healthy chicken growth and improves production.
• the broiler growth estimation with the help of linear regression, support vector regression, and Bayesian artificial neural network used for broilers’ growth estimation.
• The detecting lameness in broilers include decision trees and linear regression, it also employed for the timely detection of these diseases

Floor distribution with machine vision

• For assessing production management and animal health and wellbeing, commercial bedding floor poultry buildings, bird density, and distribution pattern are crucial considerations. Currently, the daily regular inspection of the distribution of broiler flocks in commercial grow-out houses is performed manually, which requires a lot of time and work.
• Artificial Vision: In the processing of poultry, the use of artificial vision enables real-time yield monitoring of highly valuable chicken parts, enabling managers to give quick feedback to staff who may fix any potential deficiencies. A standard way that may be used to compare outcomes across shifts, workers, and processing facilities is artificial vision. This method is especially useful for large businesses with various locations. With the aid of high-speed cameras and machine vision, Woody Breast Detection can recognize and/or sort breast fillets at regular line speeds without touching or harming the fillets. As the fillets move along and drop off a conveyor, the rigidity of the muscles is assessed. Cutting trajectories are generated for automated poultry processing systems using 3D bird deboning cutting virtual reality. At the Georgia Tech Research Institute, it is being developed. Initially conducted on models, testing is now being done on live birds

Deep learning techniques

The great advantage of using deep learning is the reduced need for feature engineering since deep neural networks are directly involved in the extraction of intrinsic attributes, i.e., color, shape, and texture information

The use of deep learning in poultry health and welfare management is on the rise, especially, dl-based approaches, including Faster R-CNN, You Only Look Once (YOLO), and Single Shot multibox Detector (SSD)have been applied for object detection in poultry in recent years

• An automated chicken counting method with Dense CNN.
• Automate the classification of vocalizations of laying hens and cattle.
• Single Shot multibook Detector, to automatically diagnose broilers’ health status
• RNN, LSTM, and GTU to detect poultry eating behaviour based on vocalization signals with an accuracy of 96.00 %
• DNN model to predict oviposition events for individual broiler breeders for efficient bird management with the area under the receiver operating characteristic (ROC) curve deep neural networks (DNNs) to estimate the gender ratio of chickens, and the experimental results achieved an average accuracy of 96.90 %. Similarly, a performance comparison of CNN, LSTM, and GRU was performed to determine chicken gender

Artificial Intelligence (AI): AI is being used to analyse large datasets and make predictions about poultry health and performance. AI-driven systems can detect early signs of diseases, manage flock behaviour, and optimize resource allocation, sound of distress or discomfort to aid in monitoring bird wellbeing, efficient and accurate in diagnoses. Other areas for AI include feed formulation optimization, genetic selection and hatchery management.

Robots : Robotic technology that uses artificial intelligence to help farmers make data-driven decisions about broiler production could result in a healthier, more productive growing environment. Use robotics to encourage the birds to be more active to increase muscle mass, which ultimately drives better improvements when it comes to the feed conversion ratio.

• Robots offer not only increase productivity and profits but their presence can also contribute to improved health and welfare. Some robots will continuously scratch the litter to eliminate caking and wet spots, reducing the incidence of pododermatitis, foot burn and breast burn. Others can monitor and map ammonia, temperature and humidity levels throughout the house

Applications of vocalization analysis due to its good performance and low computational cost to optimize conditions of the poultry environment and detect behavioral problems, i.e., feather pecking, feed intakes, infections, and stress. Thus, sound technology has real potential for practical commercial implementation to improve health and poultry welfare.

The clustering technique K-means application is more common in poultry welfare management. Application of clustering techniques in poultry health and welfare management include monitoring chicken floor distribution, behaviour monitoring, diagnosing diseases and optimizing the segmentation process. The K-means method to classify poultry into sick, normal, and active to boost a classifier while analysing chicken behaviour characteristics, i.e., speed, ability to snatch food, and resting time. the ammonia concentration in poultry farms.

Computer vision applications to poultry breeding farm processes (health and welfare management) include chicken behaviour analysis, welfare and resource management and hen tracking. Others are disease detection and diagnosis and weight or growth prediction.

Disease diagnosis in birds using modern technology:  These technologies help veterinarians and researchers identify and manage diseases in avian populations more effectively. Here are some of the modern technologies and methods used for diagnosing diseases in birds.

• PCR is a molecular biology technique that amplifies DNA and RNA sequences. It is widely used in bird disease diagnosis to detect the presence of specific pathogens, such as avian influenza virus, Newcastle disease virus, and many others. PCR allows for highly sensitive and specific detection.
• NGS technologies, like Illumina sequencing, enable the rapid sequencing of entire genomes and transcriptomes of avian pathogens
• DNA barcoding involves sequencing a short, standardized region of DNA to identify species or subspecies of birds. It can be useful in identifying the source of outbreaks and tracking the spread of diseases
• Remote sensing and GIS technologies can be used to monitor bird populations in the wild and track disease outbreaks. Remote sensing can detect changes in bird behaviour, while GIS helps in mapping and analysing disease distribution
• Artificial intelligence and machine learning These technologies can be used to analyse large datasets, such as bird migration patterns or disease prevalence, to identify trends and potential outbreak hotspots
• Audio -Analytic -Software detect respiratory disease– New analytical software can detect symptoms of laryngotracheitis, infectious bronchitis
• Nanoscale biosensors and other nanotechnologies are being developed to detect pathogens quickly and accurately in bird samples. Nanotechnology plays a pivotal role in the mechanism of tracking virus entry. The single virus tracking technology (SVT) makes it possible to track the different stages of a single virus in its life cycle, thus providing dynamic insights into the basic process of virus occurrence in living cells it help in trap avian flu viruses for early detection.

Gene editing

Gene editing technology can potentially be used in poultry to address various challenges in the industry. The CRISPR/Cas9 system is among the gene editing technologies that are creating a rapid change in poultry genomics for both poultry breeding and food production purposes (Doran et al., 2017).

The CRISPR/Cas9 system used to  

• Feed conversion, digestibility, increased egg production, growth, and overall improved performance of birds.
• Increased bird’s immunity
• Disease resistance,
• Producing birds that are leaner with little or no fat deposition in poultry meat for better nutritional profiles.
• Increase food safety and production.
• CRISPR-Cas9, researchers can then edit the genes of chickens to introduce these sex-specific markers. For example, they could insert a fluorescent marker gene that is only expressed in male embryos
• Increasing the performance of birds by enhancing muscle growth is another important agricultural application of crispr/cas9-mediated gene editing in poultry species.
• The production of therapeutic antibodies against antigens is now possible through humanized chicken for therapeutic applications. The loxpsite was inserted into the variable region of the immunoglobulin heavy chain using the crispr/cas9-mediated approach (dimitrov et al., 2016).
• Production of these genome-edited chickens will provide numerous opportunities for the discovery of therapeutic antibodies: a game-changer in biomedical research.

Sex Determination:

Sexing poultry eggs using modern technology is a valuable practice in the poultry industry, as it allows for the selective hatching of male and female chicks. This can help reduce the unnecessary culling of male chicks, which is common in traditional hatcheries. There are several methods and technologies for sexing poultry eggs, and some of them includes

• Candling: Candling involves shining a bright light through the egg to observe the developing embryo. Modern candling equipment includes automated systems that use cameras and image processing software to detect the gender of the embryo based on the differences in male and female embryonic development. Male embryos may develop at a different rate or have distinct characteristics that can be identified through these systems.
• DNA-Based Sexing: This method involves extracting DNA from the eggshell or the embryo itself and analyzing it to determine the gender. Polymerase chain reaction (PCR) is commonly used for DNA-based sexing. This method is highly accurate but may require specialized equipment and expertise.
• Biomarker Detection: Some research has focused on identifying specific biomarkers or proteins that are associated with gender differences in the egg. Modern technology can be used to detect and analyze these biomarkers, providing a non- invasive method of sexing
• Infrared Spectroscopy infrared spectroscopy technology can be used to analyze the composition of the eggshell and its thickness, as well as the gas content within the egg. Gender differences in these aspects can be used to determine the sex of the embryo
• In ovo sexing of chicken eggs by fluorescence spectroscopy
• Ultrasound Imaging High-resolution ultrasound imaging can be used to visualize the developing embryo within the egg. Differences in anatomical features between male and female embryos can be detected using this method
• Machine Learning and Artificial Intelligence, Modern technology also leverages machine learning and artificial intelligence algorithms to analyze various data points, such as eggshell texture, size, and shape, to predict the gender of the embryo

ovo sexing of chicken eggs by fluorescence spectroscopy

The following innovations will now primarily affect the nutritional research focus:

• Feed formulation software and feeding programmes
• Novel feed ingredients and feed additives
• Gastro-intestinal conditioners for gut health, birds’ welfare and food safety
• Modern technologies for feed processing and feeding packages
• Perinatal nutrition and epigenetic programming
• Advances in AI could lead to a better understanding of the poultry gut microbiome.
• In recent years, the microbiome has captured the attention of researchers, who have linked the microbial makeup of the gut to a variety of poultry diseases and other conditions affecting flock health.
• The health of the gut microbiome, a collection of microorganisms present in the gastrointestinal tract, can be affected by changes in raw materials, diet, additives, vaccine programs and farm management practices.
• Techniques of in-ovo-nutrition
• Antibiotic Alternatives: Due to concerns about antibiotic resistance, there is a growing emphasis on finding alternatives to antibiotics in poultry farming.
• Probiotics, prebiotics, and other natural supplements are being used to promote gut health and disease resistance in birds

Data Management: Digital platforms and software solutions are used for data management and analysis. Farmers can collect, store, and analyze data related to feed, water consumption, environmental conditions, and more.

Traceability: Digitalization allows for the tracking of individual birds and batches throughout their lifecycle. This traceability is crucial for quality control and food safety.

Supply Chain Optimization: Digitalization helps streamline supply chains by providing insights into demand forecasting inventory management, and logistics. The digitalization of certification and documentation processes can ease access to international markets by ensuring compliance with various regulations

The blockchain technology holds promise for modern poultry farming, it’s important to note that implementing blockchain solutions requires investment in infrastructure, training, and collaboration among industry stakeholders.  The automation, digitalization, and big data have transformed the poultry industry into a more efficient, data-driven, and sustainable sector. These advancements improve production, quality, and overall value chain management, making it an essential part of modern poultry farming

Conclusion:

Modern poultry farming technology continues to evolve as the industry seeks to improve efficiency, animal welfare, and sustainability while meeting the growing global demand for poultry products. The automation has helped to greatly increase operational capacity. the use of computer-based technology in the production of eggs, meat, and feed has produced a large amount of data on all operations. On poultry farms, automation can take the place of physical labor for routine jobs like managing litters, administering vaccinations, and monitoring the welfare of the birds contributing significantly to its value chain

References

1. Dimitrov, L., Pedersen, D., Ching, K. H., Yi, H., Collarini, E. J., Izquierdo, S., et al. (2016). Germline gene editing in chickens by efficient CRISPR-mediated homologous recombination in primordial germ cells. PLoS One 11:e0154303. doi: 10.1371/journal.pone.0154303
2. Doran, T., Challagulla, A., Cooper, C., Tizard, M., and Jenkins, K. (2017). Genome editing in poultry—opportunities and impacts. Natl. Inst. Biosci. J. 1,1–8. doi: 10.2218/natlinstbiosci.1.2016.1742

Innovative technology and practices transforming India’s poultry farming sectors