Search results for "N20 Agricultural machinery and equipment"
showing 3 items of 3 documents
Following Hydrogen Cyanide in the Valencian Country (1907-1933): Risk, Accidents and Standards in Fumigation
2019
Abstract Pests had represented a major problem in agriculture for centuries, but the huge changes in the food chain around the late nineteenth century intensified their effects in a totally unprecedented way and many new chemical substances were introduced in the attempt to control them. In this paper I will focus on the implementation of hydrogen cyanide, a highly toxic pesticide which has not received particular consideration from researchers to date. I shall analyse the introduction of this pesticide in the Valencian Country and focus on the attention given to the safety of workers and consumers. I aim to examine the role of the poison in its different uses and analyse the impact of each…
Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images
2021
Abstract Anthracnose is one of the primary diseases that affect olive production before and after harvest, causing severe damage and economic losses. The objective of this work is to detect this disease in the early stages, using hyperspectral images and advanced modelling techniques of Deep Learning (DL) and convolutional neural networks (CNN). The olives were artificially inoculated with the fungus. Hyperspectral images (450–1050 nm) of each olive were acquired until visual symptoms of the disease were observed, in some cases up to 9 days. The olives were classified into two classes: control, inoculated with water, and fungi composed of olives inoculated with the fungus. The ResNet101 arc…
Discrimination of common defects in loquat fruit cv. ‘Algerie’ using hyperspectral imaging and machine learning techniques
2021
Abstract Loquat (Eriobotrya japonica L.) is an important fruit for the economy of some regions of Spain that is very susceptible to mechanical damage and physiological disorders. These problems depreciate its value and prevent it from being exported. Visible (VIS) and near infrared (NIR) hyperspectral imaging was used to discriminate between external and internal common defects of loquat cv. ‘Algerie’. Two classifiers, random forest (RF) and extreme gradient boost (XGBoost), and different spectral pre-processing techniques were evaluated in terms of their capacity to distinguish between sound and defective features according to three approaches. In the first approach the fruit pixels were c…