You can’t deny that technology helps us work smarter. It can decrease labor needs and costs by providing greater access to information, enabling timely and informed decision making, among other things.
We have seen the explosion of computers and hand-held devices in the last decade using technologies that have increased computational and analytical capacities for less money. This creates opportunities for acquiring, storing and analyzing digital data that is playing out across every facet of our lives, including along the global produce and floral supply chain.
What might have taken three of four people to collect wash water quality data in a packinghouse or processing plant, can be done with a single computer and properly arrayed sensors. An aerial drone equipped with digital cameras can now make daily passes through an orchard in advance of harvest to discern fruit maturity. Certainly, technology can offer operators alternatives for performing certain operational tasks or replacing conventional practices that require less direct labor input. Among these are:
Supplier selection and management . Increasingly operators in our industry are moving away from a vertical integration business model and becoming more reliant on service providers and suppliers to perform key functions. A grower might employ a fertilizer company to spread fertilizers in fields, a seedling company to provide transplants, a pesticide application company to spray crops when needed, work crews to weed or thin crops, a harvest company to harvest the crop and finally a shipper to cool and sell the crop. Virtually every permutation of this scenario occurs across our industry scanning the extremes from growers owning or operating every aspect of production to only focusing on the growing of the crop. To execute internal and external tasks through suppliers and vendors requires ample communication and data sharing. Using software to manage vendors and communicate needs, track operations or analyze data to determine next steps is becoming more commonplace every day.
Real time data collection and analysis. Sensors, tablets, smart phones, cameras, and more, are just a few of the devices produce and floral companies are using to collect data in their operations. Improved wireless sensor and reader technologies are capable of tracking a product from field-to-kitchen so inventory and storage conditions are manageable in real-time to bring the highest quality product to consumers. Sensors are one of the primary technologies used in precision agriculture. The primary function of sensors is to gather and transmit data , often remotely, using instruments that detect electrical, chemical, electrochemical, magnetic, optical, or vibrational signals. Sensor technology is rapidly expanding as the cost continues to decline while reliability and accuracy improves. With wireless capabilities, sensors can directly transmit data as it is collected, making it actionable in or near real-time, and in specific locations. In Australia, researchers are using a fully automated robot containing a variety of active sensors that collects data as it wheels over a field. Guided by one person, the robot accomplishes data gathering tasks on field and crop conditions in a fraction of the time that whole teams of technicians typically take using the traditional manual methods to gather the same data. Its adjustable, lightweight frame is designed to accommodate multiple sensors and digital cameras and to breakdown into smaller units for easy transport. With its high-resolution optics, researchers see this robot as a more economical alternative to use of drones in commercial fields.
Genetics and working smarter. As the agricultural industry focuses on feeding the world’s growing population, scientists are drilling down to the molecular level to improve crop yields. In doing so, researchers are hoping to create models and other tools to help farmers maximize the genetic potential of crops. In order to do this, scientists first need to understand how a plant’s genetic makeup (genotype) affects how a plant looks and responds to its environment (phenotype). Using plant images and other physical data, researchers perform a comprehensive assessment of a plant’s genetic traits compared to its growth pattern in the field under certain soil and climatic conditions. This practice, called phenotyping , strives to use this data to develop high-performance crops that are optimally suited for soil types and climate. Genetic information is also used to select optimal plant traits is marker assisted breeding. Using genetic material native to the plant of interest, marker assisted breeding allows breeders to more rapidly screen a much larger population of a plants’ DNA for the desired traits compared to conventional breeding. This method significantly reduces the time it takes to create a new variety. In looking to the future, massive amounts of plant phenotyping data will enable development of models to predict how plants will respond to variation in environmental conditions and their specific architectures, i.e. height, branching, fruit set, etc.
Identify and fix problems quickly. One of the ways companies can become more efficient and productive is to increase the pace of problem solving. Investing in technology that identifies and solves problems quickly can provide a company an edge over its competitors. Computers commonly detect problems by monitoring continuous data streams looking for deviations from standard, predicted, or expected results. Walmart’s centralized analytics system tracks store inventory and sales among other data at each of its 20,000 locations. If there is a significant difference in sales of a particular item among stores, the system alerts analysts who review the data to identify the reason. The computers are able to drill down through the huge quantity of data and pick up small problems that often go undetected when dealing with vast amounts of data.
Might a “smarter” supply chain be on the horizon? The produce industry has pursued traceability and product coding systems for a number of years with the Produce Traceability Initiative (PTI). The ultimate goal of many of these programs enable a smarter supply chain; one where products can be tracked and traced for more efficient recalls in the case of a food safety crisis or inventories can be better managed to insure best quality to customers. In the last year or so, the potential for the blockchain has emerged as the next evolution of traceability and, ultimately, supply chain transparency. Nathaniel Popper and Steve Lohr have characterized the blockchain as a “bookkeeping method that chains together entries so that they are very difficult to modify later. It provides a way for large groups of unrelated companies to jointly keep a secure and reliable record of their transactions.” Walmart is one of 400 companies to join up with IBM to develop blockchain for tracking products. Similarly, Microsoft is working with JP Morgan Chase and a consortium of 30 companies on a competitive approach for blockchain. As the momentum to explore blockchain technology inevitably comes to the produce and floral industries, it will be critically important to focus on the advantages the technology might offer. Greater transparency on product movements can permit analyses to uncover inefficiencies in product distribution and pinpoint choke points.
Futurists are predicting that within the next 15 years, supply chains will be completely autonomous and self-orchestrated with manual labor replaced by drones, robots and unmanned trucks with AI computers running the operations. Clearly, new technology opportunities are arising every day that can help the entire supply chain work smarter and reduce labor inputs.