Enrichment of putative plant growth promoting microorganisms in biodynamic compared with organic agriculture soils.

The potential of soils to maintain biological productivity, defined as soil health, is strongly influenced by human activity, such as agriculture. Therefore, soil management has always been a concern for sustainable agriculture and new methods that account for both soil health and crop yield must be found. Biofertilization using microbial inoculants emerges as a promising alternative to conventional interventions such as excessive mineral fertilization and herbicide use.

Nutrient deficiency effects on root architecture and root-to-shoot ratio in arable crops.

Plant root traits play a crucial role in resource acquisition and crop performance when soil nutrient availability is low. However, the respective trait responses are complex, particularly at the field scale, and poorly understood due to difficulties in root phenotyping monitoring, inaccurate sampling, and environmental conditions. Here, we conducted a systematic review and meta-analysis of 50 field studies to identify the effects of nitrogen (N), phosphorous (P), or potassium (K) deficiencies on the root systems of common crops.

RootPainter: deep learning segmentation of biological images with corrective annotation.

Convolutional neural networks (CNNs) are a powerful tool for plant image analysis, but challenges remain in making them more accessible to researchers without a machine-learning background. We present RootPainter, an open-source graphical user interface based software tool for the rapid training of deep neural networks for use in biological image analysis. We evaluate RootPainter by training models for root length extraction from chicory (Cichorium intybus L.

Simulating Root Growth as a Function of Soil Strength and Yield With a Field-Scale Crop Model Coupled With a 3D Architectural Root Model.

Accurate prediction of root growth and related resource uptake is crucial to accurately simulate crop growth especially under unfavorable environmental conditions. We coupled a 1D field-scale crop-soil model running in the SIMPLACE modeling framework with the 3D architectural root model CRootbox on a daily time step and implemented a stress function to simulate root elongation as a function of soil bulk density and matric potential. The model was tested with field data collected during two growing seasons of spring barley and winter wheat on Haplic Luvisol.

Digging roots is easier with AI.

The scale of root quantification in research is often limited by the time required for sampling, measurement, and processing samples. Recent developments in convolutional neural networks (CNNs) have made faster and more accurate plant image analysis possible, which may significantly reduce the time required for root measurement, but challenges remain in making these methods accessible to researchers without an in-depth knowledge of machine learning. We analyzed root images acquired from three destructive root samplings using the RootPainter CNN software that features an interface for corrective annotation for easier use.

Kinesthetic engagement in Gestalt evaluation outscores analytical 'atomic feature' evaluation in perceiving aging in crystallization images of agricultural products.

There is an increasing interest in a systemic approach to food quality. From this perspective, the copper chloride crystallization method is an interesting asset as it enables an estimation of a sample's 'resilience' in response to controlled degradation. In previous studies, we showed that an ISO-standardized visual evaluation panel could correctly rank crystallization images of diverse agricultural products according to their degree of induced degradation.

Bacteria utilizing plant-derived carbon in the rhizosphere of Triticum aestivum change in different depths of an arable soil.

Root exudates shape microbial communities at the plant-soil interface. Here we compared bacterial communities that utilize plant-derived carbon in the rhizosphere of wheat in different soil depths, including topsoil, as well as two subsoil layers up to 1 m depth. The experiment was performed in a greenhouse using soil monoliths with intact soil structure taken from an agricultural field.