From Detection to Protection: The Role of Optical Sensors, Robots, and Artificial Intelligence in Modern Plant Disease Management.

In the past decade, there has been a recognized need for innovative methods to monitor and manage plant diseases, aiming to meet the precision demands of modern agriculture. Over the last 15 years, significant advances in the detection, monitoring, and management of plant diseases have been made, largely propelled by cutting-edge technologies. Recent advances in precision agriculture have been driven by sophisticated tools such as optical sensors, artificial intelligence, microsensor networks, and autonomous driving vehicles.

The Nuances of Plant Disease Severity Estimation Using Quantitative Ordinal Scales-Lessons Learned over Four Decades.

We revisit the foundations of the Horsfall-Barratt (HB) scale, a widely cited and applied plant disease visual assessment tool introduced in 1945, a full 37 years prior to T. T. Hebert's 1982 critique that raised concerns regarding the scale's rationale, particularly its reliance on the Weber-Fechner law and visual perception assumptions.

Understanding the ramifications of quantitative ordinal scales on accuracy of estimates of disease severity and data analysis in plant pathology.

The severity of plant diseases, traditionally defined as the proportion of the plant tissue exhibiting symptoms, is a key quantitative variable to know for many diseases but is prone to error. Plant pathologists face many situations in which the measurement by nearest percent estimates (NPEs) of disease severity is time-consuming or impractical. Moreover, rater NPEs of disease severity are notoriously variable.

Disease Incidence-Severity Relationships on Leaflets, Leaves, and Fruit in the Pecan- Pathosystem.

The most destructive disease of pecan in the southeastern United States is scab, caused by . Incidence (I)-severity (S) relationships have not previously been characterized in this pathosystem, but incidence measures can save time and should have higher accuracy compared with estimates of severity. Ten scab-susceptible cultivars and seedling trees were assessed for I and S of scab on fruit (1,972 trees) and foliage (compound leaves and leaflets, 1,129 trees) between 2010 and 2014.

Plant Disease Severity Assessment-How Rater Bias, Assessment Method, and Experimental Design Affect Hypothesis Testing and Resource Use Efficiency.

The effect of rater bias and assessment method on hypothesis testing was studied for representative experimental designs for plant disease assessment using balanced and unbalanced data sets. Data sets with the same number of replicate estimates for each of two treatments are termed "balanced" and those with unequal numbers of replicate estimates are termed "unbalanced". The three assessment methods considered were nearest percent estimates (NPEs), an amended 10% incremental scale, and the Horsfall-Barratt (H-B) scale.

What interval characteristics make a good categorical disease assessment scale?

Plant pathologists most often obtain quantitative information on disease severity using visual assessments. Category scales have been used for assessing plant disease severity in field experiments, epidemiological studies, and for screening germplasm. The most widely used category scale is the Horsfall-Barratt (H-B) scale, but reports show that estimates of disease severity using the H-B scale are less precise compared with nearest percent estimates (NPEs) using the 0 to 100% ratio scale.

Probability of detecting nematode infestations for quarantine sampling with imperfect extraction efficacy.

For quarantine sampling, it is of fundamental importance to determine the probability of finding an infestation when a specified number of units are inspected. In general, current sampling procedures assume 100% probability (perfect) of detecting a pest if it is present within a unit. Ideally, a nematode extraction method should remove all stages of all species with 100% efficiency regardless of season, temperature, or other environmental conditions; in practice however, no method approaches these criteria.