Published in Engineering, this meta-analysis covering 154 papers systematically compares transgenesis (TG) and genome editing (GE) for animal trait improvement. GE delivers larger, wider-ranging gains in growth and disease resistance yet shows taxon-specific effects. Trait enhancements weaken with animal age and in F1 offspring. The findings offer evidence for lab technique refinement and agricultural biotechnology policy-making.

This report covers a China Agricultural University study published in Engineering, which builds a BDS-IMU aided multimodal feature framework for 3D farm obstacle detection. The system cuts training sample reliance by 30%–40%, hits an overall 96.01% F₁ score and 16.56 FPS. It maintains reliable perception for unseen zero-sample agricultural obstacles, effectively easing heavy data annotation burdens and balancing detection accuracy, real-time performance and data efficiency for farm machinery autonomous navigation.

Worried about hidden meat spoilage risks in cold chains? This new study in Engineering develops a microwave sensor paired with machine learning to spot ammonia, a key rot marker, without damaging meat samples. It fixes reading errors caused by shifting temperature and humidity, cutting detection error to only 0.06 ppm and boosting accuracy by 31.11%. The wireless device works up to 12 meters away, offering a practical tool for real-time fresh meat quality tracking across storage and transport.

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.

A research team has developed a visible-light photocatalyst that nearly doubled hydrogen production by decorating cadmium sulfide (CdS) nanoparticles with carbon quantum dots (CQDs) derived from cellulose.

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.