Results 41 to 50 of about 321,230 (311)

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

Best prediction of yields for long lactations [PDF]

Journal of Dairy Science, 2009
Lactation records of any reasonable length now can be processed with the selection index method known as best prediction (BP). Previous prediction programs were limited to the 305-d standard used since 1935. Best prediction was implemented in 1998 to calculate lactation records in USDA genetic evaluations, replacing the test interval method used since ...
J B, Cole, D J, Null, P M, Vanraden
openaire   +2 more sources

Crop yield prediction integrating genotype and weather variables using deep learning.

, 2020
Accurate prediction of crop yield supported by scientific and domain-relevant insights, is useful to improve agricultural breeding, provide monitoring across diverse climatic conditions and thereby protect against climatic challenges to crop production ...
Tryambak Gangopadhyay, Baskar Ganapathysubramanian, Ganapathysubramanian, Baskar, Soumik Sarkar, Gangopadhyay, Tryambak, Shook, Johnathon, Singh, Asheesh, Wu, Linjiang, Asheesh K Singh, Linjiang Wu, Johnathon Shook, Sarkar, Soumik   +11 more
core   +2 more sources

Crop yield prediction integrating genotype and weather variables using deep learning

, 2021
Accurate prediction of crop yield supported by scientific and domain-relevant insights, is useful to improve agricultural breeding, provide monitoring across diverse climatic conditions and thereby protect against climatic challenges to crop production ...
Ganapathysubramanian, Baskar, Gangopadhyay, Tryambak, Shook, Johnathon, Singh, Asheesh, Wu, Linjiang, Sarkar, Soumik   +5 more
core   +1 more source

An Empirical Method for Prediction of Cheese Yield [PDF]

Journal of Dairy Science, 2002
Theoretical cheese yield can be estimated from the milk fat and casein or protein content of milk using classical formulae, such as the VanSlyke formula. These equations are reliable predictors of theoretical or actual yield based on accurately measured milk fat and casein content.
C, Melilli, J M, Lynch, S, Carpino, D M, Barbano, G, Licitra, A, Cappa   +5 more
openaire   +2 more sources

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