Reproduction control is another important tool for flock management in dairy sheep

With average costs of roughly 1.50€ per each tag, it is the cheapest method among the three. However, it suffers from one disadvantage which could lead to several problems. Its application to the ear lobe of the sheep increases its possibility to be lost due to entanglement in bushes, trees fences, etc. Another problem has to do with the ease of removal of the tag, a practice used in various fraudulent activities regarding animal identifications and could be avoided using irremovable animal tagging systems. In case of tag losses, new tags are to be applied, which not only causes additional administrative work but also impacts the welfare of the sheep which have to undergo another piercing of the ear.In this case, the EID is enclosed in a ceramic bolus, which is then inserted into the sheep’s rumen using a designated tool . Although having a slightly higher cost of about 4–5€, its main advantage is its permanence and very low malfunction and loss rate. Boluses have widespread use and are currently applied routinely in many commercial farms. It is however a more complicated EID to insert, with sheep needing to reach a certain age in order to safely receive the bolus. Size reduction and proper insertion by trained personnel mitigate these problems, with the bolus total size and length being a key factor. As shown by Hentz et al. , smaller boluses could be inserted safely and efficiently to smaller ewes while retaining the internal positioning and reliability.Widely used in house pets and horses for animal identification, its use in livestock although permitted is very limited . The main reason for its limited use is the difficulty to remove the EID in the abattoir,and the tendency of early models to migrate from the original region of injection.Different studies however show limited migration patterns of modern glass and silicone enclosed injectable EIDs during their use in field conditions.A particular advantage of injectable EID is the possibility of it being used not only as passive information storage but also as a sensor for physiological parameters.

The use of temperature detecting injectable passive RFID/ EIDs is widespread in the management of smaller laboratory animals and was tested on bigger farm animals under different conditions . Its use in sheep has been shown to provide highly correlating data to that of core temperature measured via rectal thermometry. This concept is, however, stackable flower pots still in the experimental stage and its future applications are uncertain.Sensors applied on the individual animal are one of the key principles of PLF with tools such as pedometers and rumination tags are well known to dairy cattle farmers. They provide information on animal’s physiological conditions whether in real time or via data loggers downloading in key passages . These sensors collect data from the animal and translate it into physiologic status such as ovulation or lameness relevant to farm management . In case of extensive sheep farming, wearable sensors have been experimented in small-scale-controlled conditions as well as experimental farms . The main objectives of these sensors are to evaluate grazing and resting behaviours, which provide information regarding grazing patterns and feed intake as well as animal position and movement of the flock . Currently, two main types of technology are being tried in this field: accelerometers, especially the tri-axial type, and GPS systems. The third use of active sensors is in the case of social networks and behaviour such as heat and mating identification. Being a seasonal breeding species, a big focus in Mediterranean production is dedicated to out of the season mating in order to maintain constant milk production in contrast to the sheep’s natural cycle . Currently, a common practice is the use of a harness on the flock rams with colour for visual identification of covered ewes; however, the use of electronic activity logger is being tested .A system that measures movement in terms of the direction and speed of the sensor is attached to the foot, neck or head of the sheep. Evaluated by the software first, data are provided to the producer to assist in decision making .

The most useful data come from three axial accelerometers which record movement in a three-dimensional pattern. Field trials confirm the ability of such accelerometers to register movement patterns linked to behaviours such as resting, grazing, moving and running/playing or lameness . Even though accelerometers could be considered technologically matured, data interpretation and validation is still a subject for field research . Meanwhile, the collection and management of the data as well as energy supply to systems in the field present a big challenge for a widespread application. In recent years, the amount of research put into this system is growing increasingly especially in attempt to take a research ready prototype into commercial production . Therefore, accelerometers could represent in the near future a viable product.Especially when paired with geographic information system , it provides information on animal movement and disposition in certain geographical areas. Such a system could help evaluate the movement of sheep in a vast grazing area, between water sources, low and high land and in response to the presence of predators or wild herbivores . In the work of de Virgilio et al. , combined use of accelerometers and GPS/GIS was proposed as a PLF option for sustainable range land management. Such systems, however, are not yet operational in commercial farming due to relative high cost of each sensor and the need for high energy supply . Also, information gathered by the systems still needs interpretation and given the right value in a decision-making process.In a recent study by Mozo et al. , tri-axial was used accelerometer with specific software to detect rams’ mating activity providing a possible tool to measure service capacity of rams. A more mature system is the electronic Alpha-Detector which includes a harness for the ram with an active reader and transmitter which detects the ewes’ EID and transmits the data to a centralized computer. The transmitted data could be interpreted for frequency of mating, true and false coverings and the number of ewes covered. This system has currently passed the research phase and is being tried in field conditions for commercial production .

Other technologies include a concept produced by Laca regarding extensive management of animals which incorporates GPS, satellite communication of data from ‘mother collars’, short distance communication between the animals’ collars and feed management based on the elaborated data. The system is very complex and requires both costly technologies and knowledge of the herd dynamics for the identification of key individuals in their respective groups . The feasibility of such system is becoming widespread in Mediterranean dairy sheep farming due to cost and complexity, but may be relevant for other types of extensive farming that use larger grazing areas , or less contact with the animal . Other sensors include microphone and sound analysis of chewing sheep and monitoring urination in sheep and cattle in order to determine liquid and nitrogen emissions. However, the systems were only described as an experimental process and not yet ready for field implementation.Stationary sensors are another key element in the PLF concept, with different types of sensors such as temperature sensors, cameras, weights and automatic feeders are placed in key locations of a barn . These sensors collect data and usually communicate with the animals’ EIDs, providing real-time data for each single animal to feedback systems . In extensive sheep farming, there are several stationary tools such as AD, weighting crates or a walk over weight system. Although the systems are extensively tested and reached advanced stages of development, they are not yet accepted by dairy sheep farmers for widespread commercial use .An AD, in simple terms, is an automat system centred around a selective gate with the ability to distinguish and direct the passage of animals. Most of the AD systems are based on the recognition of animals’ EIDs as the selective criteria. In extensive sheep farm, ADs and EIDs could be used together not only for data collection and feeding control but also as a tool to reduce manual labour for the flock . Animal selection is one of the most labour intensive activities on the farm, especially in events such as sheering, parasite treatments and selection for sale.

Automatic drafters could also be coupled with weighting systems in order to measure the condition of a single sheep, directing lower weight animals towards supplemented feeding areas accordingly .Originally developed for grazing cattle, both systems were consequently adopted and modified of sheep farming as well. The WOW was tried in field conditions where it proved its efficiency, consequently expanding its use to sheep management . The system includes a one-way passage leading to a key stimulant which the animals are forced to pass through. The weighting platform is placed in this corridor, and it communicates with the animals’ EIDs on each passage. Data regarding each single sheep are stored and could be matched against similar passages in a single day creating a more reliable result. When used by itself, the WOW system helps to reduce labour with fewer personal needed for animal sorting activity while pairing it with AD systems can allow better control on supplementation feeding . This combination has been proven to be efficient in several studies as presented by a recent review by Rutter and by Gonzalez-Garcia et al. , making it a viable instrument for farm management. The WC on the other hand is used by actively separating single animal by operator closing doors in a passage corridor. This way, each animal is weighted standing still and isolated from others. In the WC, the RFID identification could be done both by handheld transponders or by fixed reading antennas,flower pots for sale consequentially allowing the analysation of data in real time. Commercial models are already available on the market . The collected data could be used for various purposes such as ensuring lambs are ready for sale or anthelmintic treatments. The last use is of particular importance considering the growing awareness to the amount of anthelmintic resistant parasites in grazing sheep and the health implications derived from it . For this purpose, coupling the WC with a self-dosing fluid dispenser is a currently viable option with commercial products already on the market such as Te Pari fluid dispenser .

Virtual fencing is an innovative method for extensive animal management that replaces physical barriers with electronically placed boundaries. Animals are prevented from passage by a system of visible and/or audible cues combined with electric stimulus. Although VF is not able to provide a full sealing of an area, its flexibility and potential applications has attracted a growing amount of researches as well as stimulating commercial development with products such as BoviGuard, NoFence and eShepherd™. The main advantage of such a system is not the complete exclusion of animals from certain areas, but rather the possibility VF provides to guide and move the animals according to pasture availability . However, VF cannot completely replace all fences, as the hermetic exclusion of animal is impossible without physical barrier. Therefore, due to security reasons and property rights , the external fences of the pasture remain necessary. By using visible and audio cues prior to the electric stimulus VF systems are aiming to condition the animals to understand the limits of their area. Although there is a variability among the individual animals in understanding these limits, as a group the herd maintains its position . There are several factors however, which limit the adoption of VF systems on commercial farms. The first is its cost, although the cost of the system was estimated in 200 000 £ for 100 animals in UK, its difference is not as big in comparison with traditional fencing costs in the same country . However, VF cannot completely replace traditional fencing and a combined use will be always needed . Another weakness is the lack of technological infrastructure in sheep farms ; this includes network coverage and IT-related skills and understanding. Without this, farmers may find it difficult to trust hi-tech systems .

The layered architecture for designing the system enables self-independence between layers

SDSS benefited from the greater public availability of spatial data and the more flexible software, which enables its integration/- modelling into the geographic information system. In addition, an open-source SDSS project known as MicroLEIS DSS aids agriculture soil protection and land sustainability. It comprises valuable tools and techniques for decision-making in a wide range of agro-ecological schemes. This system builds on statistics, databases, neural networks, expert systems, Web technology, and GIS applications. The SDSS for agricultural land management, helps in decision making for the land management of food crops. It also aids in testing, validating and sensitivity checking of the decision models. The study revealed that SDSS is developed on Compromise Programming modules to produce spatial information integrated with fuzzy set and analytic hierarchy. SDSS utilises input information in operation, for instance, information from field experts and its applications. Whilst noticeable progress has been made in digital support systems, nonetheless, most of the proposed DSS have been put forward to handle aspects related to precision agriculture, irrigation management and optimal farming. Additionally, not much, if at all, have been proposed around facilitating support for farmers in terms of addressing their enquiries, questions and complaints, and optimising the whole process efficiently, besides providing insights to the beneficiaries from the vast amount of historic data, and recorded experience. The aim of this study, therefore, is to design and develop a system by considering the unique requirements of the farmers into accessing information whilst enhancing the overall system’s usability and acceptability. That is, the proposed DSS enables farmers to access information and experts’ advice; for example,hydroponic net pots information regarding the choice of seeds to sow, optimal harvesting times, knowing how to treat and combat plant diseases and pests, weather/calamity based forecasting and advisory etc.

The system is designed using a client–server architecture, where the client-side is responsible for all user interactions with the system. Clients interact with the server through web services. The Server applications are deployed on server machines along with a storage for managing data sets. Apart from these services, the Agro Support Analytics system also provides user registration and login functionality. A user can interact with the online Agro Support Analytics Central Server from the client machine through a web browser. The Agro Support Analytics Central Server handles input connections from clients as well as it hosts user registration and login services. In order to execute user requests the Agro Support Analytics Central Server is connected to more back-end services; i) Farmer Complaint service, ii) Historical Search service, iii) Analytics Apps. The overall working of the client/server system is illustrated in Fig. 2.Software applications of Agro Support Analytics have been designed on the configuration and plugin-based mechanism. This mechanism facilitates support for new workflow management systems and algorithms without altering the core of the system. Since the scope of the project is broad and complex; the overall project requirements can be divided into different applications with varying degrees of independence between the applications. Each application is further divided such that the application logic and business logic can be executed across servers. Moreover, the system under consideration requires faster network communications, high reliability, and excellent performance. In order to fulfil these design requirements, the n-tier architecture, or multi-layered software architecture is employed where each of the layers corresponds to a different level of abstraction. The N-tier or multi-layered approach is particularly suitable for developing web-scale and cloud-hosted applications very quickly and relatively risk-free. N-tier application architecture provides a model by which developers can create flexible and reusable applications. By segregating an application into tiers, developers acquire the option of maintaining, modifying, or adding a specific layer, instead of reworking the entire application.

In practice, the tiered architecture greatly simplifies the management of the software infrastructure. In this project, the layered architecture followed is ’closed’, meaning a request should go through all layers from top to bottom. Since architecture is broken up into multiple layers, the changes that need to be made should be more comfortable and less extensive than having to tackle the entire architecture.In a given layer, software components that belong to a similar level are organised horizontally, where the components may depend on the processing of each other, and this also makes relevant components to stays in a single compatible layer. This allows for a clean separation between types of components and also helps gather similar programming code together in one location. By isolating the layers, they become independent from one another. In the layered architecture, although the components from one layer can interact with the components of another layer, but they do not directly depend on other layer’s components. Traditional enterprise systems use RDBMS while the NoSQL system is widely adopted due to its excellent performance and high availability for large sets of distributed data. Thus if, for example, we want to change the database from SQL to NoSQL , this will cause a significant impact on the database layer, but that won’t impact any other layers. The adapted layered architectural pattern reduces the communication overhead caused by network traffic to provide faster network communications and efficient system performance. The component-based layered architecture also makes the testing process simple and convenient as individual components from each layer can be tested separately.This consists of a back-end database service comprising of various types of data sets, files, and the database management system that manages and provides access to the project data.

The datasets are made accessible to the Information and Analysis Services layer by hosting them on the Cloud. The second major functionality considered in AgroSupport Analytics is a Farmer Complaint Registration and Expert Response system. This system involves the development of interfaces for the online complain management, which can be remotely accessed to queries. These complaints can be reviewed by experts to provide feedback or suggestions using Expert web-forms. In order to store farmer complaints and associated experts’ responses, a new OnLine Farmer Complain and Expert Response dataset storage is established to contain richer data as compare to the available historical complaints data acquired from the Egyptian agricultural departments. Based on this data, extended analysis and predictions could be made possible that goes beyond the natural language based textual processing. Other datasets comprise User Profile and Login Info that includes the profile and login information of the users and user logs and activity history that contains the activities and logs of the Users. The layer also includes Agro Big Data Storage that contains the Historical Complain Dataset, the Online Farmer Complain and Expert Response Dataset. Search and Analytics Services in the Service layer interacts with this dataset in order to extract information from it.The Information and Analysis Services layer contains back-end software components and provides authentication, persistency, and information services. The authentication is a RESTful web service that operates on top of the User Data Info dataset in the private cloud and authenticates the users. Depending on the authentication result, user access type, and privileges, the user is given access to the modules in the application layer. The Complaint Management Services interfaces between the Online Complain Management application and the Online Farmer Complain and Expert Response dataset can provide functionalities such as crawl the datasets; make a model based on the structure of dataset; and store both data sets and outcomes, data dictionaries including possible parameters’ values, such that these are query-able by other tools and services, and store and index the image files associated with data sets.

The Search Service provides a mechanism to directly query datasets from the Agro Big Data Storage for querying, indexing, and searching based on Historical Search Engine as well as Farmer Complain and Expert Response Data. The Analytic and External Weather Projections services will act as information services and provide an interface between Analytic apps and the Agro Big Data Storage. Based on the Analytic apps information request, these services can query the Agro Big Data Storage dataset and then can apply data-mining, visualization, and machine learning algorithms on the data and then return the information to the Analytic apps.This layer contains user-friendly front-end interfaces designed for farmers and experts to remotely access the web components containing static as well as dynamic content. The front-end content is rendered by the web browser. These components include the User Sign In and Sign Up module, Farmer and Expert Dashboards, and Online Complain Management System. User Sign-In and Sign-Up components are available to authenticate the valid system users. After Sign In, Users can view Dashboards that contains their previous activity and up-coming notifications. In the Online Complain Management System, Farmer can submit their new complaint along with the textual, audio, and imagery data. The complaints are reviewed by the Experts, and they provide feedback or suggestions using Expert interface. These web forms are supported both in Arabic and English texts. This layer also includes Historical Search Engine and Analytics Apps. Using the Historical Search Engine component,blueberry grow pot users can query the Search Services, which in turn calls the Agro Big Data Storage to find the closest response from Historical Complain Datasets. The Analytics Apps can include analysis and predictions on the existing and/or external data sources to identify and explore patterns of ‘cause effect relationships’. The Querying Service is designed as a web service to be invoked over HTTPS to interact with the Agro Big Data storage, as shown in Fig. 5. This service-oriented approach provides the option to expose the server-side functionality to the client application. It enables a transparent and easy setup for providing desired functionality to users as well as external services within an authenticated session. The implementation of Querying Service starts with user verification that utilises the identity retrieval method provided by the Agro Support Analytics gateway. This feature not only secures the system by authenticating all the incoming requests but is also useful for maintaining logs of user activities. After user authentication, Querying Service initiates a query-building phase.

The implementation of the query-building involves i) parsing of parameters provided by the user, ii) selection of appropriate data sets.To interact with the query and complaint management component farmer needs to register with system if he is a new user or he can enter his login credentials to see the query and complaint management page. The system sends an automated email to the farmers email upon his registration. After registration/login, farmer can see a dashboard, where they can see list of all previous queries or complaints that are submitted. For each query or complaint, a status parameter is available with three possible values, i.e., ‘unresolved’, ’in-process’, or ‘resolved’. When a new query or complaint is submitted, its status is set as ‘unresolved’ by the system. This status can later be changed as ‘resolved’ by the agroexpert or by the farmer upon the resolution. Whenever the status is changed, the system sends an automated email to the farmer’s email regarding the change in the query or complaint status. In order to raise a new query or complaint, the farmer presses a ‘‘New Query or Complaint” button and a new form appears where the farmer enters the title of the query or complaint along with a detailed description in free text. Farmers can also relate their query or complaint with several filters available on the web-page. For example, farmers can add information regarding his area or region and can associate their query or complaint with one of the categories such as profitable crops for a region, irrigation, harvesting procedures and timings, management issues, pest issues, plant diseases, weather/calamity-based issues, etc., as shown in Fig. 4. Farmers also have the option to relate their query with a crop and attach images or audio files related to the issue they are facing. The additional information that the farmer provides will help the supervisor/admin later to assign them to the appropriate agro-expert. After the successful submission, the farmers’ dashboard appears with the status of the new query or complaint marked as ‘unresolved’. Farmers have the option to click on a query or complaint to view its details and responses made by agro-experts and he can make multiple top-ups on a query or complaint before it gets ‘resolved’.Supervisor can view a list of all farmers and the queries or complaints submitted by them. When a new farmer registers with the system, supervisor receives an automated email.

Hierarchical clustering was performed on 12 variables and this allowed four clusters to be retained

Like other countries in Sub-Saharan Africa where guinea fowl originated from, Benin, which is a country with a population of around 10 million people , is also involved in indigenous guinea fowl production. Mishra et al. ; Sayila and Traore et al. in their various studies found that guinea fowls are generally more resistant than chicken and turkey to most of the common poultry viral diseases such as Newcastle disease, Fowl pox and Gumboro. Guinea fowls are also well adapted to traditional breeding production systems and as such occupy an important position among rural farming households . Guinea fowl contributes immensely to rural households as it serves as a source of animal protein , income generation from the sale of eggs and birds, and thus improving the food security condition and consequently poverty reduction among rural households . Guinea fowl meat and eggs are an excellent choice, both gastronomically and dietetically, with a high protein and low fat content . Apart from income generation and nutritional  benefits, guinea fowl perform social and cultural roles in many African societies . Despite the socio-economic importance of guinea fowl in this region, it is faced with some challenges which hamper its optimum production among rural folks. Some of the challenges as documented by Traore et al. include a high rate of mortality particularly during the rainy season. Furthermore, earlier studies examined constraints to optimal poultry farming among households in the Sudanian and Sudano-Guinean areas of Benin. However, in the Guinean zone and selected districts in Sudanian and Sudano-Guinean zones, constraints on optimal guinea fowl production have received little attention from researchers. Also, dutch bucket hydroponic as guinea fowl farming is gaining prominence across all the three climatic zones in Benin and the scarcity of documented information about their socioeconomic correlates and characteristics across the country limit actions to improve and develop its production.

The aim of this study, was to gather data on indigenous guinea fowl farming practices in Benin and generate information that could enhance intervention strategies to combat the constraints and consequently improve the productivity of guinea fowl in Benin.The study was carried out during the second half of 2019. A cross sectional survey was carried out in the district outlined in Figure 1. Primary data was obtained through the administration of a questionnaire to each of the 165 local guinea fowl farmers sampled who reared at least 10 birds on their farm. Information on socio-economic characteristics of farmers, flock size, breeding and herd management technique as well as challenges against optimal production were elicited. Interview guide in local language was furthered employed among farmers as the majority were illiterates. This made it easy to validate the responses obtained from the respondents. In term of reproductive parameters, the hatch rate was computed by asking farmers the number of eggs laid by the birds per laying season and the number of eggs hatched. The mortality rate at one week and three months after hatching were also obtained as a ratio of the total number of dead birds to the total numbers of birds available atone week and three months respectively.The data collected was entered into Excel 2013, before being imported into the R software for statistical analysis. Multiple Correspondence Analysis was used to obtain a representation of farms in the form of projections of plans defined by the first-factor axis as adapted from Audigier et al. . Based on the coordinates of the farms on the main factorial axis, an Ascending Hierarchical Classification was used to group the farms according to their proximity to one another as adapted from Kouassi et al. . Descriptive statistics were used to summarize socio-demographic characteristics as well as other quantitative variables of the poultry farms surveyed. Chi-square test was used to test whether there is a significant difference or not in the farmers’ socio-demographic characteristics across regions and also if guinea fowl production indices differ across regions or not.

Non-parametric Kruskall-Wallis test was used to compare the means of guinea fowl production indices across regions. The significance threshold adopted was 5%.Guinea fowl rearing in the study area was largely dominated by men while very few women were involved as shown in Table 1. In terms of educational qualification, about one-third of the sampled farmers were illiterate while 36.4%, 26.1% and 3.0% had primary, secondary and tertiary education respectively. In addition, Atacora and Alibori regions had more illiterate farmers than the remaining eight regions. The highly educated guinea fowls farmers were found in Collines, Atlantique, Mono and Zou regions. There were no religious discrimination in the rearing of guinea fowl in the study area as it cut across all the religious groups in existence in the study area. However, it was prominent among christians than the other two religious groups. Other livelihood activities than guinea fowl farming among the respondents include crop farming , trading and art and craft . Specifically, of all the regions surveyed, the Alibori region had the lowest number while Atacora had the highest number of guinea fowl farmers.The cumulative contribution to the total inertia of the three selected factorial axis for hierarchical clustering was 92.88%. The frequencies of the different variables relating to the 4 categories of farmers are presented in Table 8. Cluster one was made up of 16.97% of the farmer sampled and were mainly located in the Alibori region. Most of the farmers were illiterate, that is, had no form of formal education and majority also had a minimum of 20 years experience in guinea fowl farming. The farmers in this cluster employed natural method of egg incubation and no additives were added to the birds’ feed and water to combat heat stress. The main and secondary activities of these farmers were livestock farming and crop farming . Extensive method of farming was largely employed by farmers in this region. Cluster 2 involved 25.45% of the farmers sampled. Most of the farmers had a minimum of 20 years farming and were located much more in the region of Atacora and Donga . The farmers in this group were mostly men. They were mostly illiterate and relatively young, as their age ranged between 25 and 50 years .

The average number of eggs used in setting up their farm was between 10 and 50 eggs. In terms of heat stress management by farmers in this cluster, only 7.1% of the farmers used additives in the birds’ drinking water. Most of the farmers engaged in cropping as their main activity and animal husbandry as a secondary activity. Furthermore, 69% of these farmers had shelters for their birds to protect them from harsh weather condition and rest. This feature made them to rear their birds under a semi-intensive system of production. Eggs were also incubated naturally by farmers in this group. Cluster 3 was made up of 24.85% of the farmers sampled. The farmers were mostly men and had primary education . More than half of the farmers in this group had relatively little farming experience in guinea fowl production. Majority of these farmers engaged in animal production as their main activity whereas 73.2% made crop production their secondary activity. The majority of farmers in this group did not add any additive to the feed or to the water of guinea fowl to manage heat stress. Cluster 4 in comparison to other groups, involved 32.73% of the farmers interviewed. These farmers were found mainly in the region of Collines , Atlantique and Zou . They were mostly male and between 25 and 50 years of age . Very few had no formal education with 37%, 44.4 % and 9.3% each having primary, secondary and university education respectively. The production system was largely semi-intensive in nature with very few running an intensive system. Animal husbandry was essentially the secondary activity of farmers in this group while crop farming was their main activity. Artificial incubation was practiced by very few of the farmers.The predominance of men in guinea fowl production as deduced from the study may not be unconnected to the difficulty involved in managing guinea fowl due to the wild instinct that guinea fowl exhibits. This instinct,dutch buckets system which is not very malleable constitutes a major constraint for the women in its production. This finding aligns with the earlier studies carried out in Ivory Coast ; Burkina-Faso and Ghana that found that guinea fowl farmers were predominantly men. Similar findings were reported in Togo , Niger and Zimbabwe . More attention on gender is required in policy design since women’s engagement in integrated farming is undeniable. This same observation is common in most African countries.

The study therefore emphasized the design and translation of technical manuals into local language due to the farmers’ low level of formal education as this will facilitate better understanding of the birds management requirement and subsequently lead to a sustainable development of this sector. Guinea fowl farming however does not present any religious and cultural limits that could hinder its production in rural areas as deduced from the study. This agrees with the earlier submission of Kone et al. and Kouassi et al. . Guinea fowl farmers engaged in other activities to diversify sources of income to meet up with the needs of their families. This result is in agreement with the findings of Traore et al. . The age of the farmers were between 25 and 50 years which was similar to the earlier report of Traore et al. that young people under 20 did not have enough resources to go into guinea fowl production. Farmers received more support from their children which are the employees as family labor. To this end, these farmers take the opportunity to pass on their knowledge and prepare them to take over. Good experience must therefore be documented by reinforcing them with innovative practices to boost the sector to respond more effectively to food security within rural households and in response to climate change, as also evidenced by Fotsa .In the majority of farms surveyed, farmers preferred to use the local hen to guinea fowl for incubating eggs due to their good brooding traits. The use of hens in villages for hatching guinea fowl eggs has been widely reported in other previous studies . In addition, guinea fowl and hen farming are closely linked . Most often, hens are used to incubate the guinea fowl’s eggs. Sometimes farmers also make use of other poultry species such as duck and turkey for the incubation . The feed stuffs used in formulating the diets of guinea fowl in Benin included corn, sorghum, millet, fonio and sometimes rice.

These diets are supplemented in some farms with maggot and termites. This gesture of giving a few handfuls of these feed to the birds was done to train the birds so as to return to the farm after free-ranging. While on free range, guinea fowl also feed on insects and grasses, which further diversified their diet. Traore et al. in Burkina Faso and Kouassi et al. in Ivory Coast, reported that the feed stuffs used for guinea fowl comprised sorghum, millet and corn. These results are different from those obtained in India where rice is the main diet offered to guinea fowl. These findings show that the choice of feed be offered to guinea fowl depends on the local availability and accessibility of the ingredients. The drinking water of guinea fowls was mostly non-drinkable. The lack of drinking water combined with the relentless distribution of mainly energy feed and kitchen waste to guinea fowl constitute factors that reduce the productivity of guinea fowl in rural areas. This same observation has been reported in Togo through the work of Lombo et al. who submitted that guinea fowl receive mainly energy feeds, thus affecting their productivity. Guinea fowl farming was intended to provide additional income to households while providing them with low cholesterol meat . These households were also concerned about the sustainability of the sector by investing in the continuity of the flock. An earlier study reported that guinea fowl production contributes to the cultural and religious ceremonies of certain sociolinguistic groups, including the annual Ditamari festival . This study revealed that bonds of friendship and fraternity are strengthened through the use of guinea fowl as gifts to friends and also, in recognition of services rendered.