The Digitalisation of African Agriculture Report 2018-2019

An inclusive, digitally-enabled agricultural transformation could help achieve meaningful livelihood improvements for Africa’s smallholder farmers and pastoralists. It could drive greater engagement in agriculture from women and youth and create employment opportunities along the value chain. At CTA we staked a claim on this power of digitalisation to more systematically transform agriculture early on. Digitalisation, focusing on not individual ICTs but the application of these technologies to entire value chains, is a theme that cuts across all of our work. In youth entrepreneurship, we are fostering a new breed of young ICT ‘agripreneurs’. In climate-smart agriculture multiple projects provide information that can help towards building resilience for smallholder farmers. And in women empowerment we are supporting digital platforms to drive greater inclusion for women entrepreneurs in agricultural value chains

Estimation of secondary soil properties by fusion of laboratory and on-line measured vis-NIR spectra

Visible and near infrared (vis-NIR) diffuse reflectance spectroscopy has made invaluable contributions to the accurate estimation of soil properties having direct and indirect spectral responses in NIR spectroscopy with measurements made in laboratory, in situ or using on-line (while the sensor is moving) platforms. Measurement accuracies vary with measurement type, for example, accuracy is higher for laboratory than on-line modes. On-line measurement accuracy deteriorates further for secondary (having indirect spectral response) soil properties. Therefore, the aim of this study is to improve on-line measurement accuracy of secondary properties by fusion of laboratory and on-line scanned spectra. Six arable fields were scanned using an on-line sensing platform coupled with a vis-NIR spectrophotometer (CompactSpec by Tec5 Technology for spectroscopy, Germany), with a spectral range of 305-1700 nm. A total of 138 soil samples were collected and used to develop five calibration models: (i) standard, using 100 laboratory scanned samples; (ii) hybrid-1, using 75 laboratory and 25 on-line samples; (iii) hybrid-2, using 50 laboratory and 50 on-line samples; (iv) hybrid-3, using 25 laboratory and 75 on-line samples, and (v) real-time using 100 on-line samples. Partial least squares regression (PLSR) models were developed for soil pH, available potassium (K), magnesium (Mg), calcium (Ca), and sodium (Na) and quality of models were validated using an independent prediction dataset (38 samples). Validation results showed that the standard models with laboratory scanned spectra provided poor to moderate accuracy for on-line prediction, and the hybrid-3 and real-time models provided the best prediction results, although hybrid-2 model with 50% on-line spectra provided equally good results for all properties except for pH and Na. These results suggest that either the real-time model with exclusively on-line spectra or the hybrid model with fusion up to 50% (except for pH and Na) and 75% on-line scanned spectra allows significant improvement of on-line prediction accuracy for secondary soil properties using vis-NIR spectroscopy

Towards Developing an Online Social Media-based Mobile Learning System

The advancement of Information and Communication Technology (ICT) and the Internet revolution gave rise to the several learning technologies on the web and mobile platform. During the last decade, the social media network became available for users to socialise and collaborate among peer group. Hence, The integration of e-learning and social media using mobile device as access point is to allow for learning and collaboration anytime, anywhere. This study seeks to provide learning on the social network platform for users to view the application on a mobile device and also foster collaboration among scholars. The system was developed using an open source Content Management System (CMS) Wordpress and Buddypress running on a WAMP or XAMPP server. MySQL was used as database. The usability of the System on the different mobile devices used was evaluated by identifying the usability attributes; designing a questionnaire based on those attributes and then analyzing the results with Statistical Package for Social Science (SPSS). The results showed that the learning system had a good usability score on mobile device

BUDGET PLANNER: USER-ORIENTED WHOLE-FARM BUDGETING SOFTWARE

Budget Planner is a whole-farm or enterprise budgeting software program that is simple to use for farmers, extension agents, and other budgeters who are sometimes inexperienced, but that also provides the detail necessary to be accurate. Program defaults eliminate repetitive questions that change little from budget to budget. Defaults can be temporarily overridden, or they can be permanently changed with a detailed modify program. The program leads a user through a sequence similar to that a producer might utilize. Input forms were created to enlarge the user clientele and eventually increase computer use by farmers and extension agents.Farm Management,

Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications

The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any "thing" we may be interested in. Wireless sensor networks (WSN) are well suited for long-term environmental data acquisition for IoT representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a range of long-term environmental monitoring IoT applications. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring application

Exploiting the Internet Resources for Autonomous Robots in Agriculture

Autonomous robots in the agri-food sector are increasing yearly, promoting the application of precision agriculture techniques. The same applies to online services and techniques implemented over the Internet, such as the Internet of Things (IoT) and cloud computing, which make big data, edge computing, and digital twins technologies possible. Developers of autonomous vehicles understand that autonomous robots for agriculture must take advantage of these techniques on the Internet to strengthen their usability. This integration can be achieved using different strategies, but existing tools can facilitate integration by providing benefits for developers and users. This study presents an architecture to integrate the different components of an autonomous robot that provides access to the cloud, taking advantage of the services provided regarding data storage, scalability, accessibility, data sharing, and data analytics. In addition, the study reveals the advantages of integrating new technologies into autonomous robots that can bring significant benefits to farmers. The architecture is based on the Robot Operating System (ROS), a collection of software applications for communication among subsystems, and FIWARE (Future Internet WARE), a framework of open-source components that accelerates the development of intelligent solutions. To validate and assess the proposed architecture, this study focuses on a specific example of an innovative weeding application with laser technology in agriculture. The robot controller is distributed into the robot hardware, which provides real-time functions, and the cloud, which provides access to online resources. Analyzing the resulting characteristics, such as transfer speed, latency, response and processing time, and response status based on requests, enabled positive assessment of the use of ROS and FIWARE for integrating autonomous robots and the Internet

Security and Privacy for Green IoT-based Agriculture: Review, Blockchain solutions, and Challenges

open access articleThis paper presents research challenges on security and privacy issues in the field of green IoT-based agriculture. We start by describing a four-tier green IoT-based agriculture architecture and summarizing the existing surveys that deal with smart agriculture. Then, we provide a classification of threat models against green IoT-based agriculture into five categories, including, attacks against privacy, authentication, confidentiality, availability, and integrity properties. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving technologies for IoT applications and how they will be adapted for green IoT-based agriculture. In addition, we analyze the privacy-oriented blockchain-based solutions as well as consensus algorithms for IoT applications and how they will be adapted for green IoT-based agriculture. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the security and privacy of green IoT-based agriculture

IoT-based systems for soil nutrients assessment in horticulture

Soil nutrients assessment has great importance in horticulture. Implementation of an information system for horticulture faces many challenges: (i) great spatial variability within farms (e.g., hilly topography); (ii) different soil properties (e.g., different water holding capacity, different content in sand, sit, clay, and soil organic matter, different pH, and different permeability) for different cultivated plants; (iii) different soil nutrient uptake by different cultivated plants; (iv) small size of monoculture; and (v) great variety of farm components, agroecological zone, and socio-economic factors. Advances in information and communication technologies enable creation of low cost, efficient information systems that would improve resources management and increase productivity and sustainability of horticultural farms. We present an information system based on different sensing capability, Internet of Things, and mobile application for horticultural farms. An overview on different techniques and technologies for soil fertility evaluation is also presented. The results obtained in a botanical garden that simulates the diversity of environment and plant diversity of a horticultural farm are discussed considering the challenges identified in the literature and field research. The study provides a theoretical basis and technical support for the development of technologies that enable horticultural farmers to improve resources management.info:eu-repo/semantics/publishedVersio

Validation of a multi-residue method to determine deltamethrin and alpha-cypermethrin in mosquito nets by gas chromatography with electron capture detection (GC-µECD)

Background: Nowadays long-lasting insecticidal mosquito nets (LNs) are frequently used around the world to protect people against malaria vectors. As they contain insecticide, laboratory control is needed to check whether the content of the active ingredient follows the conditions of the manufacturer and also if the active ingredient is still present after some time of use. For this purpose, an analytical method had to be developed. The fact that LNs include a range of polymers for the yarn and use coated or incorporated technologies for the active ingredient, it is a challenge to find only one analytical method determining the active ingredient in LNs, which takes into account both impregnation technologies. Some methods are provided by international organizations but are limited by the determination of only one pesticide per method. The aim of this study was to optimize a short time extraction method for deltamethrin and alpha-cypermethrin from coated and incorporated mosquito nets and also to detect both insecticides in one analytical run, using gas chromatography with electron capture detection (GC-mu ECD). Methods: Based on the literature, the most suitable solvent and the adequate extraction process for the insecticides used for net making were identified and adapted for the new multi-residue method. Results: The validation data of the multi-residue method to determine deltamethrin and alpha-cypermethrin in mosquito nets by GC-mu ECD are given. Depending on the concentration of the active ingredient spiked on the nets, the mean recovery for alpha-cypermethrin ranged between 86% and 107% with a relative standard deviation below 3.5%. For deltamethrin it ranged between 90% and 108% with a relative standard deviation also below 3.5%. The limit of detection is 0.009 g.a.i/kg of net (0.3 mg a.i./m(2) of net) both for alpha-cypermethrin and deltamethrin. Conclusions: Data obtained are excellent. A 30 minutes reflux extraction method with xylene was developed to determine alpha-cypermethrin and deltamethrin in long-lasting insecticidal mosquito nets (LNs) by gas chromatography with electron capture detection (GC-mu ECD). The method can be easily extended to others pyrethroid used for mosquito net treatment. This paper also presents an overview of the studies dealing with pesticide determination in mosquito nets