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A naturally ventilated poly house, also known as a naturally ventilated greenhouse, is a greenhouse structure designed to harness natural airflow for temperature regulation and climate control. Unlike traditional greenhouses equipped with mechanical ventilation systems, naturally ventilated polyhouses leverage passive ventilation techniques to maintain optimal growing conditions for crops.
Different Names:
Naturally Ventilated Greenhouses
Eco-Friendly Polyhouses
Sustainable Crop Shelters
Passive Ventilation Enclosures
Climate-Smart Growing Structures
Agricultural greenhouse and polyhouse farming have revolutionized the way we cultivate crops, providing controlled environments conducive to year-round production. Yet, even within these sheltered spaces, crops remain vulnerable to external forces, particularly in mountainous regions prone to sudden hailstorms. The consequences of hail damage extend beyond immediate financial loss, affecting livelihoods and food security. Hence, the imperative for effective crop protection measures becomes evident.
Before delving into the intricacies of shade net houses, it’s important to understand the basics of dragon fruit cultivation. Dragon fruit, also known as pitaya, is a tropical fruit that thrives in warm climates with well-draining soil. It belongs to the cactus family and has a striking appearance with its vibrant colors and unique shape. To successfully cultivate dragon fruit, several key factors must be taken into consideration. These include suitable soil pH levels, irrigation practices, and proper pruning techniques. Additionally, pollination plays a vital role in the fruiting process, making it necessary to introduce bees or other pollinators to the growing area.
Blueberry, also referred as Vaccinium myrtillus as scientific nomenclature thrives on very small shrubs, about 50 cm high, in light undergrowth with acidic soil. This plant is native to North America.
In contrast, cultivated blueberry shrubs can reach up to 2.50 m in height and produce larger fruits than their wild counterparts. Blueberry bushes require specific growing conditions; excessive wind, dryness, and alkaline soil can damage and weaken the crop.
Cultivating blueberry bushes in plastic greenhouses (tunnel type) with climate control technology and suitable soil or substrate promotes higher yield and better quality.
In the dynamic world of agriculture, blueberry farmers are always on the lookout for innovative methods to boost productivity, enhance fruit quality, and embrace sustainable farming practices. High tunnels have emerged as a revolutionary solution in blueberry cultivation, offering numerous benefits that help farmers overcome traditional challenges and seize new opportunities. This setup helps regulate temperature, humidity, and protects plants from adverse weather conditions. This comprehensive guide delves into how high tunnels can transform blueberry farming, driving higher yields and superior quality produce.
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This talk explores the integration of Knowledge Graphs (KGs) and Large Language Models (LLM) to harness their combined power for improved natural language understanding. By leveraging KGs' structured knowledge and language models' text comprehension abilities, we can leverage the domain-specific–and potentially sensitive–data together with the general knowledge of LLMs.
We also examine how language models can enhance KGs through knowledge extraction and refinement. The integration of these technologies presents opportunities in various domains, from question-answering to chatbots, fostering more intelligent and context-aware applications.
I recently created a demo for some prospective clients of mine, demonstrating how to use Large Language Models (LLMs) together with graph databases like Neo4J.
The two have a lot of interesting interactions, namely that you can now create knowledge graphs easier than ever before, by having AI find the graph entities and relationships from your unstructured data, rather than having to do all that manually.
On top of that, graph databases also have some advantages for Retrieval Augmented Generation (RAG) applications compared to vector search, which is currently the prevailing approach to RAG.