A novel 3D imaging system for strawberry phenotyping

Accurate and quantitative phenotypic data in plant breeding programmes is vital in breeding to assess the performance of genotypes and to make selections. Traditional strawberry phenotyping relies on the human eye to assess most external fruit quality attributes, which is time-consuming and subjective. 3D imaging is a promising high-throughput technique that allows multiple external fruit quality attributes to be measured simultaneously. A low cost multi-view stereo (MVS) imaging system was developed, which captured data from 360° around a target strawberry fruit. A 3D point cloud of the sample was derived and analysed with custom-developed software to estimate berry height, length, width, volume, calyx size, colour and achene number. Analysis of these traits in 100 fruits showed good concordance with manual assessment methods. This study demonstrates the feasibility of an MVS based 3D imaging system for the rapid and quantitative phenotyping of seven agronomically important external strawberry traits. With further improvement, this method could be applied in strawberry breeding programmes as a cost effective phenotyping technique

Risking the Self: Vulnerability and Its Uses in Research

As researchers, we aim to reduce emotional risk, in essence our vulnerability, that comes from empathising with others. Based on ethnographic fieldwork in India and Indonesia, and drawing on concrete examples of research with community volunteers and women municipal councillors, this chapter challenges the assumption that vulnerability in research is negative. My chapter argues that heightening one’s vulnerability is a necessary aspect of ethical knowledge production. Vulnerability means being purposefully open to being affected by the other, to have one’s very core sense of who one is and is becoming challenged in our encounters with others (e.g., research participants and research partners). While vulnerability in this sense increases risk, the benefits of becoming more not less vulnerable enriches our research and is pivotal to understanding the way power operates in the field

Inflight radiometric calibration of New Horizons’ Multispectral Visible Imaging Camera (MVIC)

We discuss two semi-independent calibration techniques used to determine the inflight radiometric calibration for the New Horizons’ Multi-spectral Visible Imaging Camera (MVIC). The first calibration technique compares the measured number of counts (DN) observed from a number of well calibrated stars to those predicted using the component-level calibration. The ratio of these values provides a multiplicative factor that allows a conversation between the preflight calibration to the more accurate inflight one, for each detector. The second calibration technique is a channel-wise relative radiometric calibration for MVIC's blue, near-infrared and methane color channels using Hubble and New Horizons observations of Charon and scaling from the red channel stellar calibration. Both calibration techniques produce very similar results (better than 7% agreement), providing strong validation for the techniques used. Since the stellar calibration described here can be performed without a color target in the field of view and covers all of MVIC's detectors, this calibration was used to provide the radiometric keyword values delivered by the New Horizons project to the Planetary Data System (PDS). These keyword values allow each observation to be converted from counts to physical units; a description of how these keyword values were generated is included. Finally, mitigation techniques adopted for the gain drift observed in the near-infrared detector and one of the panchromatic framing cameras are also discussed