Highlights•The challenges involved in the automatic identification of plant diseases are
characterised.•The impact of those challenges on current proposals is discussed.•Possible …

The severity of plant diseases, traditionally the proportion of the plant tissue exhibiting
symptoms, is a key quantitative variable to know for many diseases and is prone to error …

This paper presents a survey on methods that use digital image processing techniques to
detect, quantify and classify plant diseases from digital images in the visible spectrum …

Detecting and measuring the damage on historic glazed tiles plays an important role in the
maintenance and protection of historic buildings. However, the current visual inspection …

Early disease detection is a major challenge in horticulture. Integrated Pest Management
(IPM) combines prophylactic, biological and physical methods to fight bioagressors of crops …

Measuring the nitrogen nutrition status of plants is useful for nitrogen fertiliser management.
As nitrogen is one of the main structural components of chlorophyll, its nutrition status is …

There is intense pressure on agricultural productivity due to the ever‐growing population.
Several diseases affect crop yield and thus, effective control of these can significantly …

1. Tissue removal by herbivores (ie herbivory) is a dominant interaction in most communities
which has important impacts on natural and managed ecosystems. Despite the importance …

Convolutional neural networks (CNNs) are the gold standard in the machine learning (ML)
community. As a result, most of the recent studies have relied on CNNs, which have …

Cercospora leaf spot (CLS) poses a high economic risk to sugar beet production due to its
potential to greatly reduce yield and quality. For successful integrated management of CLS …