AIMC Topic: Plants, Genetically Modified

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In situ foliar augmentation of multiple species for optical phenotyping and bioengineering using soft robotics.

Science robotics
Precision agriculture aims to increase crop yield while reducing the use of harmful chemicals, such as pesticides and excess fertilizer, using minimal, tailored interventions. However, these strategies are limited by factors such as sensor quality, w...

Distinct actin microfilament localization during early cell plate formation through deep learning-based image restoration.

Plant cell reports
Using deep learning-based image restoration, we achieved high-resolution 4D imaging with minimal photodamage, revealing distinct localization and suggesting Lifeact-RFP-labeled actin microfilaments play a role in initiating cell plate formation. Phra...

Artificial neural networks as a tool for seasonal forecast of attack intensity of Spodoptera spp. in Bt soybean.

International journal of biometeorology
Soybean (Glycine max) is the world's most cultivated legume; currently, most of its varieties are Bt. Spodoptera spp. (Lepidoptera: Noctuidae) are important pests of soybean. An artificial neural network (ANN) is an artificial intelligence tool that ...

Structure and function of Vitis vinifera Arabidopsis Response Regulator 1 (VvARR1) protein provide insights into the regulatory mechanism of grape fruit shape through gibberellin-cytokinin crosstalk.

International journal of biological macromolecules
Grape fruit shape is a crucial agricultural trait that significantly impacts the commercial value of grapes. In this study, we developed a machine learning system to classify grape fruit shapes, offering an objective phenotypic assessment method. Mul...