Technology What the tech?

What the tech?

DEMYSTIFYING AGTECH BUZZWORDS

The demands on a grower are ever-increasing. In the world of modern farming practices, a grower must wear many hats. The hype surrounding digital agriculture continues, with technologies popping up on a daily basis determined to provide cost-effective, efficient and smarter solutions for growers. But what do all these agtech buzzwords mean? We take a look at nine of the most common concepts and what they mean.

LiDAR

LiDAR (Light Detection And Ranging), also called “laser scanning” or “3D scanning”, uses eye-safe laser beams to create 3D representations of a surveyed environment. A LiDAR sensor emits pulsed light waves into the surrounding environment. The pulses bounce off surrounding objects and return to the sensor, which calculates the distance travelled by using the time it took for each pulse to return to the sensor. LiDAR is used in agriculture to create digital elevations models (slope, elevation and aspect), vegetation models (location, canopy height), and for erosion control (water flow, catchments, soil loss).

NDVI

NDVI (Normalised Difference Vegetation Index) is a method of determining crop health by measuring the index of plant greenness, or photosynthetic activity. NDVI is calculated on a per-pixel basis as the normalised difference between the red and near infrared bands of an image. NDVI imagery helps farmers and agronomists identify variability and anomalies in their paddocks, track growth performance and create variable rate maps. NDVI can also be used to track crop growth in-season, forecast yield, understand crop dynamics and track hail, storm, drift or front events, and determine picking strategies, among others.

Blockchain

Blockchain is revolutionising and accelerating the agriculture industry’s move toward greater transparency. A type of distributed ledger which houses and manages data, Blockchain has huge benefits to agriculture including farmto-shelf tracing – which aids authenticity of products – increased transparency in supply chains, enables instant transactions, streamlines inventory management and connects in with AgTech and the Internet of Things (IoT). Having one unalterable source of information about your farm, stock and contracts could reduce inefficiencies, so that as a grower, you only have one place to record information.

Traceability

The journey of fruit is fast becoming an important one, with consumers wanting to expand their knowledge of not only where they grapes come from, but the journey they took to get from grapevine to lunchbox. Traceability allows the grape supply chain and its consumers to follow the movement of a bunch, box, pallet, container of grapes through stages of production, from growth to packing, distribution and export. Increasing traceability through Blockchain technology will help to ensure each cog in the supply chain is accountable for its role.

Internet of things (IoT)/sensors

The Internet of Things (IoT) is a network of objects connected wirelessly using sensors, which can transmit information to each other, or a wider network, without human intervention. Connected objects can include humans, animals, plants, and infrastructure (e.g., equipment, buildings). While sensing data is not new, technology advancements in cost, quality, and robustness of sensors and enabling data analysis and connectivity technologies have accelerated the potential of the IoT for agriculture. IoT allows devices across a farm to measure data remotely and provide the information to a grower in real time.

Precision farming/ agriculture

Known as precision ag/ agriculture, precision farming is the science of improving crop yields and assisting management decisions using technology and data at many stages of farming. Agricultural land is variable and grape properties are located on a huge variety of land types, with a range of soil types and soil properties. Precision farming helps identify ways to increase productivity with greater environmental constraints, optimising inputs to maximise profitability and enabling industry to respond to market opportunities. Precision farming includes the adoption of technology such as control systems, sensors, robotics, drones, and autonomous vehicles.

Big data

Big data is a term that describes the large volume of data – both structured and unstructured – that inundates businesses on a day-to-day basis. This technology is playing an progressively essential role in agriculture as the amount of information collected on and around farms increases. The ability to track physical items, collect real-time data, and forecast scenarios could be a real game changer in production practices. Big data can be processed, mined and analysed by big data and artificial intelligence (AI) applications to help growers make smart decisions about variety/crop choice, ethical chemical use, optimising farm equipment, managing supply chain issues and more.

Autonomous systems/robotics

Shorter working days, greater efficiency, better work-life balance – automation in agriculture has been creating a buzz for years. Robot harvesters, self-driving tractors, unmanned aerial vehicles (UAVs, or drones), and other autonomous systems, can support the role of the grower by completing the time-consuming or menial tasks. Many factors are precipitating the trend toward precision farming supplemented by technology (including robotics), including the cost and availability of labour, diminishing availability and increasing cost of water, political and regulatory procedures and hold-ups; limited acreage; better, cheaper and faster technological automation products; and climate change.

Nanomaterials

Nanomaterials can exist in nature or be manufactured. They are tiny – measured in nanometres, which is one billionth of a metre! Because of their very small size and unique chemical, optical, electronic or mechanical properties, nanomaterials can be used to manufacture products that are much smaller, lighter, reactive or soluble than conventional products. Currently, nanomaterials are most commonly used in medicine, environmental science and food processing, but they present opportunities in improving seed germination and growth, plant protection, pathogen detection, and pesticide/herbicide residue detection, as well as the development of intelligent food packaging.