AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Crops, Agricultural

Showing 81 to 90 of 171 articles

Clear Filters

Harnessing artificial intelligence for analysing the impacts of nectar and pollen feeding in conservation biological control.

Current opinion in insect science
Plant-derived foods, such as nectar and pollen, have garnered substantial research attention due to their potential to support natural enemies of pests. This review is a pioneering exploration of the potential for artificial intelligence approaches t...

Deep learning-based association analysis of root image data and cucumber yield.

The Plant journal : for cell and molecular biology
The root system is important for the absorption of water and nutrients by plants. Cultivating and selecting a root system architecture (RSA) with good adaptability and ultrahigh productivity have become the primary goals of agricultural improvement. ...

Based on the multi-scale information sharing network of fine-grained attention for agricultural pest detection.

PloS one
It is of great significance to identify the pest species accurately and control it effectively to reduce the loss of agricultural products. The research results of this project will provide theoretical basis for preventing and controlling the spread ...

Is deeper always better? Evaluating deep learning models for yield forecasting with small data.

Environmental monitoring and assessment
Predicting crop yields, and especially anomalously low yields, is of special importance for food insecure countries. In this study, we investigate a flexible deep learning approach to forecast crop yield at the provincial administrative level based o...

Machine learning applications to improve flavor and nutritional content of horticultural crops through breeding and genetics.

Current opinion in biotechnology
Over the last decades, significant strides were made in understanding the biochemical factors influencing the nutritional content and flavor profile of fruits and vegetables. Product differentiation in the produce aisle is the natural consequence of ...

Detecting common coccinellids found in sorghum using deep learning models.

Scientific reports
Increased global production of sorghum has the potential to meet many of the demands of a growing human population. Developing automation technologies for field scouting is crucial for long-term and low-cost production. Since 2013, sugarcane aphid (S...

Construction of deep learning-based disease detection model in plants.

Scientific reports
Accurately detecting disease occurrences of crops in early stage is essential for quality and yield of crops through the decision of an appropriate treatments. However, detection of disease needs specialized knowledge and long-term experiences in pla...

Measuring the crop water demand and satisfied degree using remote sensing data and machine learning method in monsoon climatic region, India.

Environmental science and pollution research international
Supply of water is one of the most significant determinants of regional crop production and human food security. To promote sustainable management of agricultural water, the crop water requirement assessment (CropWRA) model was introduced as a tool f...

Weed Detection Using Deep Learning: A Systematic Literature Review.

Sensors (Basel, Switzerland)
Weeds are one of the most harmful agricultural pests that have a significant impact on crops. Weeds are responsible for higher production costs due to crop waste and have a significant impact on the global agricultural economy. The importance of this...

Machine Learning-Assisted Approaches in Modernized Plant Breeding Programs.

Genes
In the face of a growing global population, plant breeding is being used as a sustainable tool for increasing food security. A wide range of high-throughput omics technologies have been developed and used in plant breeding to accelerate crop improvem...