AI Medical Compendium Journal:
Frontiers in plant science

Showing 21 to 30 of 63 articles

Enhancing Nitrogen Nutrition Index estimation in rice using multi-leaf SPAD values and machine learning approaches.

Frontiers in plant science
Accurate nitrogen diagnosis is essential for optimizing rice yield and sustainability. This study investigates the potential of using multi-leaf SPAD measurements combined with machine learning models to improve nitrogen nutrition diagnostics in rice...

Induced biochemical variations in maize parental lines affect the life table and age-specific reproductive potential of (J.E. Smith).

Frontiers in plant science
In recent years, the fall armyworm, has rapidly emerged as a global invasive pest, challenging the maize production and leading to considerable economic losses. Developing resistant hybrids is essential for sustainable maize cultivation, which requi...

Discrimination of leaf diseases in Maize/Soybean intercropping system based on hyperspectral imaging.

Frontiers in plant science
In order to achieve precise discrimination of leaf diseases in the Maize/Soybean intercropping system, i.e. leaf spot disease, rust disease, mixed leaf diseases, this study utilized hyperspectral imaging and deep learning algorithms for the classific...

AI-assisted image analysis and physiological validation for progressive drought detection in a diverse panel of L.

Frontiers in plant science
INTRODUCTION: Drought detection, spanning from early stress to severe conditions, plays a crucial role in maintaining productivity, facilitating recovery, and preventing plant mortality. While handheld thermal cameras have been widely employed to tra...

: a transfer learning based rice disease phenotype recognition platform using SENet and microservices.

Frontiers in plant science
Classification of rice disease is one significant research topics in rice phenotyping. Recognition of rice diseases such as , , , , and are a critical research field in rice phenotyping. However, accurately identifying these diseases is a challengin...

Plant science in the age of simulation intelligence.

Frontiers in plant science
Historically, plant and crop sciences have been quantitative fields that intensively use measurements and modeling. Traditionally, researchers choose between two dominant modeling approaches: mechanistic plant growth models or data-driven, statistica...

Non-destructive identification of from different geographical origins by Vis/NIR and SWIR hyperspectral imaging techniques.

Frontiers in plant science
The composition of (Tai-Zi-Shen, TZS) is greatly influenced by the growing area of the plants, making it significant to distinguish the origins of TZS. However, traditional methods for TZS origin identification are time-consuming, laborious, and des...

Accurate and fast detection of tomatoes based on improved YOLOv5s in natural environments.

Frontiers in plant science
Uneven illumination, obstruction of leaves or branches, and the overlapping of fruit significantly affect the accuracy of tomato detection by automated harvesting robots in natural environments. In this study, a proficient and accurate algorithm for ...

Multi-model genome-wide association studies for appearance quality in rice.

Frontiers in plant science
Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM an...