The CROP benchmark includes 5,045 multiple-choice questions covering three difficulty levels.

Large language models (LLMs) have demonstrated remarkable efficacy across knowledge-intensive tasks. Nevertheless, their untapped potential in crop science presents an opportunity for advancement. To narrow this gap, we introduce CROP, which includes a novel instruction tuning dataset specifically designed to enhance LLMs' professional capabilities in the crop science sector, along with a benchmark that serves as a comprehensive evaluation of LLMs' understanding of the domain knowledge. The CROP dataset is curated through a task-oriented and LLM-human integrated pipeline, comprising 210,038 single-turn and 1,871 multi-turn dialogues related to crop science scenarios. The CROP benchmark includes 5,045 multiple-choice questions covering three difficulty levels.

People eat an estimated 100 billion bananas every year, making them one of the most consumed fruits on the planet. It's hard to imagine a world without bananas – yet the possibility exists. The future banana supply at your nearest supermarket is under siege by fungal diseases. Black Sigatoka is one of the most destructive diseases to commonly grown banana cultivars. Like so many pathogens, it has developed resistance to current fungicides.

"We're trying to change how people run agronomic research. Instead of establishing a small field plot, running statistics and publishing the means, what we're trying to do involves the farmer far more directly. We are running experiments with farmers' machinery in their own fields. We can detect site-specific responses to different inputs. And we can see whether there's a response in different parts of the field," said Nicolas Martin, assistant professor in the U of I Department of Crop Sciences and co-author of the study.

HOUSTON – High-tech devices in agriculture such as unmanned aerial vehicles and sensors are leading to immense growth in data collection and deployment, and a Houston conference Aug. 20-21 will feature scholars and industry experts discussing future applications in all aspects of production agriculture. The invitation-only conference, Identifying Obstacles to Applying Big Data in Agriculture, will be held at the Houston Airport Marriott at George Bush Intercontinental Airport. It is sponsored by Texas A&M AgriLife Research and the U.S. Department of Agriculture- National Institute of Food and Agriculture. "We have had advanced technologies like GPS in agriculture for over 20 years, but only a small handful of these technologies have made a significant impact," said Dr. Alex Thomasson, conference coordinator and Texas A&M AgriLife Research engineer in College Station. "Thus we want to cast a vision for the practical use of big data in production agriculture so we can take advantage of the current wave of attendant technologies like the so-called Internet of Things, artificial intelligence, wireless communications, the cloud, etc. "This conference will feature discussion with key business leaders and academics involved in a broad range of disciplines within big data and precision agriculture.