Recent advances of hyperspectral imaging technology and applications in agriculture

B Lu, PD Dao, J Liu, Y He, J Shang - Remote Sensing, 2020 - mdpi.com
Remote sensing is a useful tool for monitoring spatio-temporal variations of crop
morphological and physiological status and supporting practices in precision farming. In …

Development of soft computing and applications in agricultural and biological engineering

Y Huang, Y Lan, SJ Thomson, A Fang… - … and electronics in …, 2010 - Elsevier
Soft computing is a set of “inexact” computing techniques, which are able to model and
analyze very complex problems. For these complex problems, more conventional methods …

Comparison of object detection and patch-based classification deep learning models on mid-to late-season weed detection in UAV imagery

AN Veeranampalayam Sivakumar, J Li, S Scott… - Remote Sensing, 2020 - mdpi.com
Mid-to late-season weeds that escape from the routine early-season weed management
threaten agricultural production by creating a large number of seeds for several future …

Application of support vector machine technology for weed and nitrogen stress detection in corn

Y Karimi, SO Prasher, RM Patel, SH Kim - Computers and electronics in …, 2006 - Elsevier
This study was conducted to evaluate the usefulness of a new method in artificial
intelligence, the support vector machine (SVM), as a tool for classifying hyperspectral …

[HTML][HTML] A review of machine learning techniques for identifying weeds in corn

A Venkataraju, D Arumugam, C Stepan, R Kiran… - Smart Agricultural …, 2023 - Elsevier
Weeds pose a major challenge in achieving high yield production in corn. The use of
herbicides although effective can be expensive and their excessive use poses ecological …

Hyperspectral reflectance imaging to classify lettuce varieties by optimum selected wavelengths and linear discriminant analysis

RH Furlanetto, T Moriwaki, R Falcioni, M Pattaro… - Remote Sensing …, 2020 - Elsevier
Lettuce (Lactuca sativa L.) has a wide variation of pigment classes and content in its leaves,
with a variety of colors, textures, and sizes, which impose difficulties for their classification …

Identification and classification of Asian soybean rust using leaf-based hyperspectral reflectance

RH Furlanetto, MR Nanni, MS Mizuno… - … Journal of Remote …, 2021 - Taylor & Francis
Asian soybean rust (Phakopsora pachyrhizi) is the most severe disease in soybean crops
production. The early detection of the disease by traditional methods involves visual …

A comparison of hyperspectral chlorophyll indices for wheat crop chlorophyll content estimation using laboratory reflectance measurements

A Bannari, KS Khurshid, K Staenz… - IEEE Transactions on …, 2007 - ieeexplore.ieee.org
The objective of this paper is to investigate the relationship between a wide range of
hyperspectral chlorophyll indices and wheat crop chlorophyll content using laboratory …

Early-Season Map** of Johnsongrass (Sorghum halepense), Common Cocklebur (Xanthium strumarium) and Velvetleaf (Abutilon theophrasti) in Corn Fields …

MP Martín, B Ponce, P Echavarría, J Dorado… - Agronomy, 2023 - mdpi.com
Accurate information on the spatial distribution of weeds is the key to effective site-specific
weed management and the efficient and sustainable use of weed control measures. This …

Towards the modeling and prediction of the yield of oilseed crops: A multi-machine learning approach

M Parsaeian, M Rahimi, A Rohani, SS Lawson - Agriculture, 2022 - mdpi.com
Crop seed yield modeling and prediction can act as a key approach in the precision
agriculture industry, enabling the reliable assessment of the effectiveness of agro-traits …