The Growing Need for Centralised Lab Data in Agri-Tech
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Agri-tech, or ag-tech, is a rapidly evolving field focused on utilising advanced technologies to increase agricultural productivity and sustainability. It is a booming market filled with R&D scientists looking to provide more farmers with tools and technologies to improve crop yields, make plants resistant to insects and harsh weather, and increase nutritional value.
With such ambitious goals comes the "stalk-high" task of creating efficient and optimised laboratory workflows that drive progress. What are the critical technologies needed to manage such an undertaking? And, just as important, how do you sync them to work effectively? In this blog, we'll highlight the importance of running a centralised agri-tech lab, some of the essential technologies in the industry, and how to integrate them all.
The Dangers of De-Centralized Data
The issue many agri-tech labs face is that much of the vast data being generated is siloed (pun intended) between several stand-alone software platforms, incapable of communicating with one another. This hinders efficiency, reproducibility, and scalability. The backbone of an efficient lab is a single, unified environment for managing all aspects of laboratory operations, from sample tracking and data management to reporting and analysis. Let's look at the key technologies in agri-tech and the features to look for in streamlining those workflows.
Key Technologies for Agri-Tech
Molecular-Based Testing
Genotyping, marker-assisted breeding, and GMO testing provide ways to identify traits that would otherwise be impossible to select based on phenotype alone. Researchers use this to develop new crops with higher yields or improved nutritional value.
- Real-World Example: Development of golden rice or better seed germination in forages like millet.
- Necessary Software Feature to Have: Visualise genetic sequences and allow for lab-wide collaboration among scientists.
Proteomics
Proteomics can be used to identify proteins that are involved in specific biological processes, such as plant stress response, nutrient uptake, metabolism, or insect resistance. This information is used to develop crops that grow in new environments or new pesticides that target specific proteins.
- Real-world Example: Aphid control in sorghum crops or canola cultivation in colder environments.
- Necessary Software Feature to Have: Fully customisable metadata fields with advanced search functions for real-time reporting.
Bioimaging & Phenotyping
Visualising biological structures at the molecular level shows how phenotypes emerge from cellular-level traits. These technologies identify and characterise desirable characteristics to study the effects of different fertilisers or pesticides on plant growth.
- Real-world Example: Disease resistance in cassava or less pesticide usage in soybean.
- Necessary Software Feature to Have: See the full history of a sample with parent-child sample relationships and see clone lineage quickly.
Soil, Feed, Fertiliser, and Water Analysis
Crops cannot flourish without the right ecological factors in place. Physical and chemical analysis of these components can be used to optimise crop yields, improve plant health, and ensure food safety.
- Real-World Example: Growing wheat or corn in extreme weather or ecological conditions.
- Necessary Software Feature to Have: The ability to send out to third-party chemical testing companies for analysis.
Let Your Agri-Tech Laboratory Bloom
The technologies available to agri-tech labs have grown by leaps and bounds, but traditional software used in the lab has not. Don't let outdated lab software hinder your agri-tech lab's growth. Discover how eLabNext's digital lab platform can elevate your research work, improve efficiency, and ensure compliance.
Take the first step to enhance your lab's performance with our personal demo or a free 30-day trial.
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