Results 31 to 40 of about 290,261 (262)

Biomass Prediction of Heterogeneous Temperate Grasslands Using an SfM Approach Based on UAV Imaging

Agronomy, 2019
An early and precise yield estimation in intensive managed grassland is mandatory for economic management decisions. RGB (red, green, blue) cameras attached on an unmanned aerial vehicle (UAV) represent a promising non-destructive technology for the ...
Esther Grüner, Thomas Astor, Michael Wachendorf   +2 more
doaj   +1 more source

Creeping Bentgrass Yield Prediction With Machine Learning Models

Frontiers in Plant Science, 2021
Nitrogen is the most limiting nutrient for turfgrass growth. Instead of pursuing the maximum yield, most turfgrass managers use nitrogen (N) to maintain a sub-maximal growth rate.
Qiyu Zhou, Douglas J. Soldat
doaj   +1 more source

Effects of canopy management practices on grapevine bud fruitfulness

OENO One, 2020
Background and aims: Bud fruitfulness is a key component of grapevine reproductive performance as it determines crop production for the following growing season.
Cassandra Collins, Xiaoyi Wang, Stephen Lesefko, Roberta De Bei, Sigfredo Fuentes   +4 more
doaj   +1 more source

Modelling the Influence of Soil Properties on Crop Yields Using a Non-Linear NFIR Model and Laboratory Data

Soil Systems, 2021
This paper introduces a new non-linear correlation analysis method based on a non-linear finite impulse response (NFIR) model to study and quantify the effects of ten soil properties on crop yield. Two versions of the NFIR model were implemented: NFIR-LN,
Rebecca L. Whetton, Yifan Zhao, Said Nawar, Abdul M. Mouazen   +3 more
doaj   +1 more source

Prediction of Crop Yield Using Phenological Information Extracted from Remote Sensing Vegetation Index

Sensors, 2021
Phenology is an indicator of crop growth conditions, and is correlated with crop yields. In this study, a phenological approach based on a remote sensing vegetation index was explored to predict the yield in 314 counties within the US Corn Belt, divided ...
Zhonglin Ji, Yaozhong Pan, Xiufang Zhu, Jinyun Wang, Qiannan Li   +4 more
doaj   +1 more source

Crop Yield Prediction

2023 4th International Conference on Intelligent Technologies (CONIT)
The fast pace of urban development minimize the agricultural lands. Owing to poor rainfall and drastic climatic changes farmers often face challenges to sustain cultivation of crops with respect to crop cycle. With growing economic competition and rising population, governmental agencies design long term plans which rarely address the farmer's needs ...
Potnuru Karthik, Bolloju Sanjith, Betha Charan Satya Raj, Gujjula Dhanush Reddy, Bhavani Vasantha   +4 more
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A Review of CNN Applications in Smart Agriculture Using Multimodal Data

Sensors
This review explores the applications of Convolutional Neural Networks (CNNs) in smart agriculture, highlighting recent advancements across various applications including weed detection, disease detection, crop classification, water management, and yield
Mohammad El Sakka, Mihai Ivanovici, Lotfi Chaari, Josiane Mothe   +3 more
doaj   +1 more source

Modeling of the Effect of Process Variations on a Micromachined Doubly-Clamped Beam

Micromachines, 2017
In the fabrication of micro-electro-mechanical systems (MEMS) devices, manufacturing process variations are usually involved. For these devices sensitive to process variations such as doubly-clamped beams, mismatches between designs and final products ...
Lili Gao, Zai-Fa Zhou, Qing-An Huang
doaj   +1 more source

Sustained Therapeutic Efficacy of Intravenous Plasminogen Concentrate in Pediatric Patients With Type 1 Plasminogen Deficiency: An Analysis of Dosing Parameters and Clinical Outcomes

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Type 1 plasminogen deficiency (PLGD‐1) is an ultra‐rare autosomal recessive disorder caused by variants in the PLG gene and affects approximately 1.6 individuals per million. The condition is characterized by decreased plasminogen levels and impaired function, resulting in fibrin‐rich lesions on mucous membranes throughout the body.
Charles Nakar, Karen Thibaudeau, Mary Mathias, Heather McDaniel, Madlen Reschke, Klaus Tenbrock, Joseph M. Parker, Amy Shapiro   +7 more
wiley   +1 more source

Personalized Zebrafish Models for Fusion‐Positive Pediatric Sarcomas

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Clinical sequencing efforts have revolutionized our approaches to categorizing pediatric cancers in real time. This has dramatically improved our ability to profile pediatric tumors, identify actionable vulnerabilities, and influence clinical care.
Lisa H. Hall, Emma N. Harrison, Genevieve C. Kendall   +2 more
wiley   +1 more source