Want a non-destructive way to map fruit internal quality? Researchers built a fully wavelength-tunable SFDI imaging system covering 450–1040 nm. This modular device captures wide-field, depth-resolved optical properties of peaches, apples and pears without mechanical scanning. It accurately predicts peach firmness and reveals uneven pigment and water distribution inside fruit flesh, offering a precise new optical tool for agricultural fruit quality inspection.

Expensive high-resolution spectral cameras hold back precise crop monitoring for farmers. A new unsupervised AI network called UDAMSR Net offers a cheap software fix. It upgrades blurry low-resolution aerial and ground crop images without matching high-quality training data. Tested on wheat across two farm sites, the tool sharpens leaf textures, preserves true spectral signals, and restores accurate chlorophyll prediction results across different sensors and flight heights. Keep reading to learn how this model cuts hardware costs for agricultural remote sensing.

Autonomous vehicles promise greener, smoother urban travel, yet their environmental pros and cons are far more complicated than many assume. This new analysis from Engineering breaks down dual carbon trade-offs: AVs cut traffic emissions via platooning and shared fleets, but heavier electric trucks and repeated vehicle platoons speed up road wear and raise infrastructure carbon costs. It also outlines targeted vehicle, road and policy fixes to balance efficiency gains and infrastructure burdens for sustainable automated mobility.

Want to test soil fertility instantly on farmland without sending samples to labs? This new Engineering commentary breaks down four mainstream field sensors tracking soil nutrients, from portable colorimetric kits to laser and γ-ray detectors. Each tool carries unique flaws: model failure across farmlands, air element interference and heavy calibration needs. Scientists now turn to AI to boost sensor performance, targeting simple, buryable detectors that measure crop-absorbable nitrogen on-site for smarter precision farming.

Photodetectors are the “eyes” of modern electronic systems, playing a vital role in fields ranging from optical communication and imaging to sensing. As technology advances, there is a growing demand for photodetectors that are not only highly sensitive but also capable of detecting a broad spectrum of light, responding rapidly, and distinguishing complex optical information. However, traditional photodetectors often face inherent limitations, such as low light absorption efficiency in thin materials, slow response speeds due to carrier trapping, and limited spectral ranges dictated by material bandgaps.

The Korea Research Institute of Standards and Science (KRISS, President Dr. Lee Ho Seong) has established purity analysis techniques and testing procedures for 15 high-purity gases used in semiconductor processes, and has developed six certified reference materials (CRMs) that verify measurement accuracy. This provides a foundation for objectively evaluating the quality of semiconductor gases domestically, moving beyond a reliance on the certificates of analysis provided by suppliers themselves.

Commercial pet foods may be an overlooked source of PFAS exposure for companion animals. We analyzed 100 dog and cat food products in Japan and found PFAS widely, with fish-derived ingredients tending to contain higher long-chain PFAS. A follow-up paired serum–food study showed that cats had higher long-chain PFCA burdens and stronger serum–food relationships than dogs, suggesting that pet food can contribute to feline PFAS exposure in household environments.