Results 91 to 100 of about 607,170 (169)

Nutritional status of wheat plant on subjected to different fertilizer treatments shown by leaf tissue tests

, 1953
Giichi Hasegawa, Takaaki Oba
openalex   +2 more sources

Mineral Nutrition and Amino-Acids in Tomato [PDF]

, 1957

openalex   +1 more source

NutritionVerse-Direct: Exploring Deep Neural Networks for Multitask Nutrition Prediction from Food Images [PDF]

arXiv
Many aging individuals encounter challenges in effectively tracking their dietary intake, exacerbating their susceptibility to nutrition-related health complications. Self-reporting methods are often inaccurate and suffer from substantial bias; however, leveraging intelligent prediction methods can automate and enhance precision in this process. Recent
arxiv  

Studies on the nutrition of rice plant with reference to Helminthosporium leaf spot : Preliminary report : III The nutrient absorption as affected by the water temperature

, 1953
Isamu BABA, Yasuo Takahashi, Iwaho Iwata
openalex   +2 more sources

SULPHUR NUTRITION OF COTTON [PDF]

, 1951
David R. Ergle, Frank M. Eaton
openalex   +1 more source

Exploring Nutritional Impact on Alzheimer's Mortality: An Explainable AI Approach [PDF]

arXiv
This article uses machine learning (ML) and explainable artificial intelligence (XAI) techniques to investigate the relationship between nutritional status and mortality rates associated with Alzheimers disease (AD). The Third National Health and Nutrition Examination Survey (NHANES III) database is employed for analysis.
arxiv  

Frequently Asked Questions (FAQ) related to the EFSA assessment of Article 14 and 13.5 health claims applications

EFSA Journal, 2009
EFSA Panel on Dietetic Products, Nutrition and Allergies
doaj   +1 more source

NUTRITION WITH PURIFIED FOOD SUBSTANCES

, 1915
E. V. McCollum, Marguerite Davis
openalex   +1 more source

Assessment of the level of nutrition. Urinary excretion of aneurin at varying levels of intake [PDF]

, 1940
Y. L. Wang, John Yudkin
openalex   +1 more source

Nutrition Estimation for Dietary Management: A Transformer Approach with Depth Sensing [PDF]

arXiv
Nutrition estimation is crucial for effective dietary management and overall health and well-being. Existing methods often struggle with sub-optimal accuracy and can be time-consuming. In this paper, we propose NuNet, a transformer-based network designed for nutrition estimation that utilizes both RGB and depth information from food images.
arxiv