Radioactivity and GMO-Free Sterile Insect Technology for the Sustainable Control of the Invasive Pest Drosophila suzukii.

Drosophila suzukii (D. suzukii), commonly known as the spotted wing drosophila, is a highly invasive crop pest that is difficult to control using chemical insecticides. To address the urgent need for alternative and more sustainable control strategies, the sterile insect technique (SIT) is improved, which involves the release of sterilized male insects to mate with fertile conspecifics, thereby reducing the size of the pest population in the subsequent generation. The three critical aspects that influence the success of SIT programs in D. suzukii are addressed. First, an accurate and nondestructive method is established to determine the sex of individual insects based on the differential weight of male and female pupae. Second, conditions for X-ray sterilization are systematically tested and an optimal dose (90 kV/40 Gy) is identified that ensures the efficient production of sterile D. suzukii for release. Finally, the inherent thermosensitivity of D. suzukii males is exploited to develop a temperature-based sterilization technique, offering an alternative or additional SIT method for this pest. These advances will contribute to the development of a comprehensive and effective strategy for the management of D. suzukii populations, reducing their impact on agriculture and helping to safeguard crop yields.

X-ray driven peanut trait estimation: computer vision aided agri-system transformation.

BACKGROUND: In India, raw peanuts are obtained by aggregators from smallholder farms in the form of whole pods and the price is based on a manual estimation of basic peanut pod and kernel characteristics. These methods of raw produce evaluation are slow and can result in procurement irregularities. The procurement delays combined with the lack of storage facilities lead to fungal contaminations and pose a serious threat to food safety in many regions. To address this gap, we investigated whether X-ray technology could be used for the rapid assessment of the key peanut qualities that are important for price estimation. RESULTS: We generated 1752 individual peanut pod 2D X-ray projections using a computed tomography (CT) system (CTportable160.90). Out of these projections we predicted the kernel weight and shell weight, which are important indicators of the produce price. Two methods for the feature prediction were tested: (i) X-ray image transformation (XRT) and (ii) a trained convolutional neural network (CNN). The prediction power of these methods was tested against the gravimetric measurements of kernel weight and shell weight in diverse peanut pod varieties1. Both methods predicted the kernel mass with R2 > 0.93 (XRT: R2 = 0.93 and mean error estimate (MAE) = 0.17, CNN: R2 = 0.95 and MAE = 0.14). While the shell weight was predicted more accurately by CNN (R2 = 0.91, MAE = 0.09) compared to XRT (R2 = 0.78; MAE = 0.08). CONCLUSION: Our study demonstrated that the X-ray based system is a relevant technology option for the estimation of key peanut produce indicators (Figure 1). The obtained results justify further research to adapt the existing X-ray system for the rapid, accurate and objective peanut procurement process. Fast and accurate estimates of produce value are a necessary pre-requisite to avoid post-harvest losses due to fungal contamination and, at the same time, allow the fair payment to farmers. Additionally, the same technology could also assist crop improvement programs in selecting and developing peanut cultivars with enhanced economic value in a high-throughput manner by skipping the shelling of the pods completely. This study demonstrated the technical feasibility of the approach and is a first step to realize a technology-driven peanut production system transformation of the future.