Heating quinoa shoots results in yield loss by inhibiting fruit production and delaying maturity.

Increasing global temperatures and a growing world population create the need to develop crop varieties that provide higher yields in warmer climates. There is growing interest in expanding quinoa cultivation, because of the ability of quinoa to produce nutritious grain in poor soils, with little water and at high salinity. The main limitation to expanding quinoa cultivation, however, is the susceptibility of quinoa to temperatures above approximately 32°C. This study investigates the phenotypes, genes and mechanisms that may affect quinoa seed yield at high temperatures. Using a differential heating system where only roots or only shoots were heated, quinoa yield losses were attributed to shoot heating. Plants with heated shoots lost 60-85% yield as compared with control plants. Yield losses were the result of lower fruit production, which lowered the number of seeds produced per plant. Furthermore, plants with heated shoots had delayed maturity and greater non-reproductive shoot biomass, whereas plants with both heated roots and heated shoots produced higher yields from the panicles that had escaped the heat, compared with the control. This suggests that quinoa uses a type of avoidance strategy to survive heat. Gene expression analysis identified transcription factors differentially expressed in plants with heated shoots and low yield that had been previously associated with flower development and flower opening. Interestingly, in plants with heated shoots, flowers stayed closed during the day while the control flowers were open. Although a closed flower may protect the floral structures, this could also cause yield losses by limiting pollen dispersal, which is necessary to produce fruit in the mostly female flowers of quinoa.

Classifying cold-stress responses of inbred maize seedlings using RGB imaging.

Increasing the tolerance of maize seedlings to low-temperature episodes could mitigate the effects of increasing climate variability on yield. To aid progress toward this goal, we established a growth chamber-based system for subjecting seedlings of 40 maize inbred genotypes to a defined, temporary cold stress while collecting digital profile images over a 9-daytime course. Image analysis performed with PlantCV software quantified shoot height, shoot area, 14 other morphological traits, and necrosis identified by color analysis. Hierarchical clustering of changes in growth rates of morphological traits and quantification of leaf necrosis over two time intervals resulted in three clusters of genotypes, which are characterized by unique responses to cold stress. For any given genotype, the set of traits with similar growth rates is unique. However, the patterns among traits are different between genotypes. Cold sensitivity was not correlated with the latitude where the inbred varieties were released suggesting potential further improvement for this trait. This work will serve as the basis for future experiments investigating the genetic basis of recovery to cold stress in maize seedlings.

Raspberry Pi-powered imaging for plant phenotyping.

PREMISE OF THE STUDY: Image-based phenomics is a powerful approach to capture and quantify plant diversity. However, commercial platforms that make consistent image acquisition easy are often cost-prohibitive. To make high-throughput phenotyping methods more accessible, low-cost microcomputers and cameras can be used to acquire plant image data. METHODS AND RESULTS: We used low-cost Raspberry Pi computers and cameras to manage and capture plant image data. Detailed here are three different applications of Raspberry Pi-controlled imaging platforms for seed and shoot imaging. Images obtained from each platform were suitable for extracting quantifiable plant traits (e.g., shape, area, height, color) en masse using open-source image processing software such as PlantCV. CONCLUSIONS: This protocol describes three low-cost platforms for image acquisition that are useful for quantifying plant diversity. When coupled with open-source image processing tools, these imaging platforms provide viable low-cost solutions for incorporating high-throughput phenomics into a wide range of research programs.

PlantCV v2: Image analysis software for high-throughput plant phenotyping.

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.

Adenoviral delivery of interleukin-10 fails to attenuate experimental Lyme disease.

Production of interleukin-10 (IL-10) by C57BL/6 mice following infection with Borrelia burgdorferi has been proposed as a mechanism whereby resistance to the development of experimental Lyme arthritis is maintained. In the current study, we sought to determine the role of IL-10 during infection of arthritis- and carditis-susceptible C3H mice. Infection of C3H IL-10(-/-) mice led to increased joint swelling and arthritis severity scores over those of wild-type C3H mice. Measurement of B. burgdorferi numbers in joints or disseminated tissues indicated a more efficient clearance of spirochetes in the absence of IL-10, similar to that reported in C57BL/6 IL-10(-/-) mice. However, in contrast to previous in vitro work, infection of C3H IL-10(-/-) mice led to decreased in vivo expression of the cytokines KC, IL-1beta, IL-4, and IL-12p70 in the infected joints. Finally, adenoviral expression of IL-10 in the infected joints of C3H mice was unable to modulate the development of severe Lyme arthritis and had no effect on spirochete clearance or Borrelia-specific antibody production. Development of Lyme carditis appeared to be independent of modulation by IL-10. These results suggest that IL-10 limits the development of joint inflammation in both arthritis-resistant and -susceptible mouse strains infected with B. burgdorferi and that increased IL-10 production cannot rescue genetic susceptibility to development of pathology in this model.