Our Software Ecosystem
With smart agriculture concept in mind, AGRINOME™ software ecosystem was designed with applications applicable to both applied research and commercial production in oil palm industry. Our AGRINOME™ solutions for R&D improve the way we analyse oil palm germplasm and searching the best combination of materials for breeding. On the other hand, our AGRINOME™ solutions for commercial increase the workflow efficiency through automation, reducing conventional steps, and increase productivity of oil palm upstream industrial processes such as seed production and seedling clonal propagation. Ultimately, these software components, namely AGRINOME™ for Breeding, Tissue Culture, Seed Production and Nursery, are integrable to from comprehensive digital crop improvement platform with the single mission to produce more with less by improving from the planting material.
For R&D and commercial.
Our AGRINOME™ solutions dedicated for R&D, namely AGRINOME™ for Breeding and Nursery, aim to harness research data to create elite planting material with desired genotype and economic traits such as high yield, disease-resistant and low palm height. These applications are relevant to be used by research scientists and breeders from universities, research institutions and plantations.
Our AGRINOME™ solutions dedicated for commercial operation, namely AGRINOME™ for Tissue Culture, Seed Production and Nursery, aim to harness production data to maximize efficiency, productivity and profitability for large-scale industrial production of commercial planting materials, and to maintain good farm management practices through data and technology. These applications are suitable to be used by researchers, operators and managers from research institutions, commercial farm and plantations.
By embracing the adoption of Industry 4.0 (I4.0), AGRINOME™’s incorporation of highly advanced technology by integrating data digitization, Artificial Intelligence (AI), Internet of Things (IoT), data analytics and automation is a major transition in the agriculture industry.
AGRINOME™ applies digital technologies such as mobile application and sensors to capture or convert signals, observations and information into digital form that can be understood by computing system and artificial intelligence. This is of crucial importance to allow high volume and variety of data in the oil palm field and nursery to be intermingled for data processing, storage and analytics, while it overcomes the limitations of having high human error rates and tedious steps when conventional data collection and management methods are used.
AGRINOME™ promotes automation with the use of control systems, such as computers, information technologies and robots, applied to every single step in oil palm research from data collection to data processing/validation, data management and data analytics. This will facilitate faster and more accurate decision when all processess and data flow are automated, ensuring better plantation management and sustainability.
Advances in cloud technologies allow user accessibility to highly scalable and borderless computer system without active management and maintenanance, especially when deadling with rapidly growing of oil palm research and plantation data, as well as demand for big data analytics for all domains of oil palm industry.
The data generated from oil palm research and plantation activities is huge. With limitations in manually analysing these data in the past, the emergence of data science and big data analytics is essential to help the scientists and agriculturists to examine their big data including structured, semi-structured and unstructured data. The technology is important to uncover valuable information such as hidden patterns, novel correlations, research insights, market trends and customer behaviours to make faster and more accurate informed decision.
Internet of Thing (IoT) is an ever-growing network of interrelated sensor devices, computing devices, machines and objects that allows exchange of data over the internet. It can be applied in oil palm farming to collect and process data in repetitive cycle and enables the agiculturists to respond to the emerging environment issues and challenges in nursery and field, either by automated way (e.g. adjust and maintain soil water content automatically to a specific level) or semi-automated way (e.g. depending on agriculturist to authorise fertilising process via mobile app).
Artificial intelligence (AI) comes into a reality when the digitisation and cloud computing come in place providing the foundation for smart analytics. By simulating human intelligence, AI can be quickly applied to predict plant disease outbreak, fruit ripening time, suggest best herbicides to use and many others, with the ultimate vision to produce more with less in accordance with increasing world population and food demands.
Powered by cloud computing, AGRINOME™ solutions are readily to be deployed allowing future scalability in both horizontal and vertical ways, ease to access and full integrability with internet of things. As alternative, our solutions are also compatible with on-premise installation connecting AGRINOME™ to your well-established data centre.
Easy to set up.
Cloud or on-premise.
The AGRINOME™ softwares can be deployed on an off-site cloud infrastructure, in which the data and configuration is held in the cloud and does not reside on the client site, but the users can have access to it through desktop or mobile browsers. Cloud solution is subscription-based and involves annual fee, where the maintenance, application update, security and uptime guarantee are provided by the cloud provider.
The AGRINOME™ softwares can be deployed on an on-premise infrastructure, in which the data and configuration is held in the in-house server physically located at an organisation’s office site or data center. This allows the organisation to have full control of their own security and access to the data/application, but the downsides of on-premise environments are the one-time server hardware setup cost, long-term maintenance cost, power consumption, space, and risk of failure/physical damage might occured from client side.