Endosulfan Resistance in Hypothenemus hampei (Coleoptera: Scolytidae) in New Caledonia

ABSTRACT The Potter tower direct spray technique was used to determine the susceptibility to endosulfan of 16 strains of Hypothenemus hampei (Ferrari) from the East and West Coasts of New Caledonia. Strains from the drier West Coast were susceptible, whereas susceptible and resistant strains were recorded from the wetter East Coast. This is the first record of resistance in H . hampei and Scolytidae. High levels of up to 1,000-fold endosulfan resistance were detected from five locations. These were associated with poor field control since 1986 and highly significant increases in berry infestation from 1985 to 1987. Detection of resistance follows 6 yr of lindane use and 10 yr of biannual endosulfan application

Simple system using natural mineral water for high-throughput phenotyping of Arabidopsis thaliana seedlings in liquid culture

Background: Phenotyping for plant stress tolerance is an essential component of many research projects. Because screening of high numbers of plants and multiple conditions remains technically challenging and costly, there is a need for simple methods to carry out large-scale phenotyping in the laboratory.Methods: We developed a method for phenotyping the germination and seedling growth of Arabidopsis (Arabidopsis thaliana) Col-0 in liquid culture. Culture was performed under rotary shaking in multiwell plates, using Evian natural mineral water as a medium. Nondestructive and accurate quantification of green pixels by digital image analysis allowed monitoring of growth. Results: The composition of the water prevented excessive root elongation growth that would otherwise lead to clumping of seedlings observed when classic nutrient-rich medium or deionized water is used. There was no need to maintain the cultures under aseptic conditions, and seedlings, which are photosynthetic, remained healthy for several weeks. Several proof-of-concept experiments demonstrated the usefulness of the approach for environmental stress phenotyping. Conclusion: The system described here is easy to set up, cost-effective, and enables a single researcher to screen large numbers of lines under various conditions. The simplicity of the method clearly makes it amenable to high-throughput phenotyping using robotics

Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts