Author: admin

Mimicking the way experienced human observers track growth over time, 3D-NOD integrates novel labeling, registration, and data augmentation strategies to boost sensitivity and accuracy. Tested across multiple crop species, the system achieved an impressive mean F1-score of 88.13% and IoU of 80.68%, offering a powerful tool for real-time, organ-level plant phenotyping.

Accurate plant growth monitoring underpins modern agriculture, enabling yield prediction, stress detection, and precise phenotyping. Traditional methods—measuring plant height, canopy volume, or detecting diseases—often rely on 2D images, which cannot fully capture depth or resolve self-occluded structures. Spatiotemporal phenotyping, which tracks individual organs over time, offers richer insights but faces challenges in detecting small, newly emerged organs and handling complex plant architectures. 3D sensing technology addresses these limitations by capturing depth information, but current 3D approaches are either computationally heavy or require organs to be large enough for tracking. Based on these challenges, the researchers developed a method to improve early-stage detection of plant growth events from time-series 3D data.

A study (DOI: 10.1016/j.plaphe.2025.100002) published in Plant Phenomics on 22 February 2025 by Dawei Li’s team, Donghua University, presents a highly sensitive 3D deep learning framework for detecting new plant organs, enabling more accurate and real-time growth monitoring to advance precision agriculture and phenotyping.

The researchers evaluated the 3D-NOD framework using a high-precision 3D plant dataset containing tobacco, tomato, and sorghum. They constructed a spatiotemporal dataset of 37 growth sequences, comprising 468 point clouds, each with over ten growth stages. Since most sequences captured seedlings, the primary growth events were budding. Using the Semantic Segmentation Editor under Ubuntu, they annotated all points under the Backward & Forward Labeling (BFL) strategy into two semantic classes—“old organ” and “new organ.” The training set included 25 sequences and the test set 12 sequences. To enhance learning, each mixed point cloud underwent Humanoid Data Augmentation (HDA) to generate ten variants for training the DGCNN backbone. Performance was assessed with Precision, Recall, F1-score, and Intersection over Union (IoU). Compared to PointNet, PointNet++, DGCNN, and PAConv, 3D-NOD achieved superior sensitivity in new organ detection, with F1 and IoU for new organs reaching 76.65% and 62.14%, respectively, despite many buds being too small for human identification. Qualitative results confirmed accurate detection of tiny buds across all three species with low false alarms. Ablation studies demonstrated that removing any key component—BFL, Registration & Mix-up (RMU), or parts of HDA—caused noticeable performance declines, underscoring their combined importance. Interestingly, detection was best in sorghum, likely due to its faster bud growth. To meet real-time phenotyping needs, the team adapted the pipeline for single point cloud testing by creating pseudo-temporal inputs, enabling inference without multiple growth stages. Comparative analyses on tomato, tobacco, and sorghum sequences showed only minor accuracy reductions compared to standard spatiotemporal testing, highlighting the framework’s versatility for both multi-stage and single-stage growth monitoring scenarios.

3D-NOD offers a robust, scalable solution for precision agriculture and breeding programs. By accurately detecting organ-level growth events early, it enables researchers and growers to monitor crop development more closely, improve trait measurements, and optimize resource use. This capability is vital for high-throughput phenotyping, where rapid and non-invasive measurement of plant traits drives selection efficiency. The framework’s adaptability to different species suggests broad potential in monitoring diverse crops under field or greenhouse conditions. Beyond agriculture, the method could inform botanical research, forestry, and ecological studies where fine-scale structural changes in plants are critical indicators of health and development.

###

References

DOI

10.1016/j.plaphe.2025.100002

Original Source URL

https://doi.org/10.1016/j.plaphe.2025.100002

Funding information

This work was supported by the self-collected funds from Dawei Li.

About Plant Phenomics

Science Partner Journal Plant Phenomics is an online-only Open Access journal published in affiliation with the State Key Laboratory of Crop Genetics & Germplasm Enhancement, Nanjing Agricultural University (NAU) and distributed by the American Association for the Advancement of Science (AAAS). Like all partners participating in the Science Partner Journal program, Plant Phenomics is editorially independent from the Science family of journals. Editorial decisions and scientific activities pursued by the journal’s Editorial Board are made independently, based on scientific merit and adhering to the highest standards for accurate and ethical promotion of science. These decisions and activities are in no way influenced by the financial support of NAU, NAU administration, or any other institutions and sponsors. The Editorial Board is solely responsible for all content published in the journal. To learn more about the Science Partner Journal program, visit the SPJ program homepage.

For centuries, humanity relied on coastal landmarks and tide gauges to understand sea levels. But satellites changed everything. Since the early 1990s, orbiting instruments have provided precise, global records of ocean surface height.

These data revealed not only how seas are rising but also how predictions from decades ago were impressively accurate.

Satellites changed sea-level tracking

Study lead author Torbjörn Törnqvist is a professor in the Department of Earth and Environmental Sciences at Tulane University.

“The ultimate test of climate projections is to compare them with what has played out since they were made, but this requires patience – it takes decades of observations,” said Törnqvist.

He noted that the team was quite amazed at how good those early projections were, especially considering how crude the models were back then, compared to what is available now.

“For anyone who questions the role of humans in changing our climate, here is some of the best proof that we have understood for decades what is really happening, and that we can make credible projections.”

Sea-level rise differs across regions

Professor Sönke Dangendorf emphasized the importance of translating global patterns into regional forecasts.

“Sea level doesn’t rise uniformly – it varies widely. Our recent study of this regional variability and the processes behind it relies heavily on data from NASA’s satellite missions and NOAA’s ocean monitoring programs,” he said.

“Continuing these efforts is more important than ever, and essential for informed decision-making to benefit the people living along the coast.”

Satellites confirm acceleration

When satellites first began tracking sea levels in the early 1990s, they showed an average increase of about one eighth of an inch per year. It was only later that scientists confirmed this pace was speeding up.

By October 2024, NASA researchers announced that the rate of rise had doubled over three decades. That moment offered the perfect opportunity to compare real-world changes against projections made nearly thirty years earlier.

Close call with predictions

In 1996, the Intergovernmental Panel on Climate Change (IPCC) released its assessment report, just as satellite monitoring began.

The report projected about 8 centimeters of sea-level rise over 30 years. The actual outcome was 9 centimeters, nearly identical.

However, the models underestimated melting ice sheets by over 2 centimeters. Back then, the destabilizing effects of warming ocean waters on Antarctic ice were poorly understood. Greenland’s ice was also flowing into the ocean faster than anticipated.

Components of sea-level rise

The study shows that thermal expansion of seawater and melting of smaller glaciers were predicted fairly well. But contributions from Greenland and Antarctica were treated as negligible.

In reality, these ice sheets accounted for nearly a quarter of observed sea-level rise. Another overlooked factor was groundwater depletion, which transferred more water to oceans than expected.

Ignoring ice-sheets caused errors

Early IPCC reports assumed that the dynamic behavior of ice sheets could be ignored for decades. This assumption proved incorrect. Later assessments that excluded dynamic ice flow produced unrealistically low projections.

Once dynamic ice loss was included, estimates increased significantly. Modern assessments now highlight the “deep uncertainty” surrounding possible ice-sheet disintegration, which could drive sea levels far higher than expected.

Past models were surprisingly accurate

Thermal expansion was slightly overestimated, which balanced out the underestimated role of ice sheets.

This created projections that, by chance, matched reality more closely than their flawed assumptions should have allowed.

Still, the overall accuracy offers confidence in today’s more advanced models, especially since early reports successfully predicted atmospheric carbon dioxide levels.

Future climate projections

Predictions made in the 1990s have proven largely accurate, but the greatest challenges still lie ahead.

Ongoing uncertainty about ice sheets and human emissions makes continuous monitoring vital for helping coastal societies prepare for what lies ahead.

“Given the advances in both resolution and process understanding since the 1990s, the early success of the IPCC-SAR projection gives considerable confidence to climate projections for the future,” wrote the researchers.

“Meanwhile, the importance of continued monitoring of all relevant components of the climate system by key agencies cannot be understated.”

The study is published in the journal Earth’s Future.

—–

Like what you read? Subscribe to our newsletter for engaging articles, exclusive content, and the latest updates. 

Check us out on EarthSnap, a free app brought to you by Eric Ralls and Earth.com.

—–

A research team has provided the first experimental proof that flat electronic bands in a kagome superconductor are active and directly shape electronic and magnetic behaviors.

Researchers from Rice University, working with international partners, have found the first clear evidence of active flat electronic bands within a kagome superconductor. The discovery marks an important step toward creating new strategies for designing quantum materials, including superconductors, topological insulators, and spin-based electronics, which could play a central role in advancing future electronics and computing.

The findings, published on August 14 in Nature Communications, focus on the chromium-based kagome metal CsCr₃Sb₅, a material that becomes superconducting when placed under pressure.

Kagome metals are defined by their unique two-dimensional lattice of corner-sharing triangles. Recent theories have suggested that these structures can host compact molecular orbitals, or standing-wave patterns of electrons, which may enable unconventional superconductivity and unusual magnetic states driven by electron correlation effects.

In most known materials, such flat bands are positioned too far from the relevant energy levels to influence behavior. In CsCr₃Sb₅, however, they play an active role and directly shape the properties of the material.

Pengcheng Dai, Ming Yi, and Qimiao Si of Rice’s Department of Physics and Astronomy and Smalley-Curl Institute, along with Di-Jing Huang of Taiwan’s National Synchrotron Radiation Research Center, led the study.

“Our results confirm a surprising theoretical prediction and establish a pathway for engineering exotic superconductivity through chemical and structural control,” said Dai, the Sam and Helen Worden Professor of Physics and Astronomy.

The finding provides experimental proof for ideas that had only existed in theoretical models. It also shows how the intricate geometry of kagome lattices can be used as a design tool for controlling the behavior of electrons in solids.

“By identifying active flat bands, we’ve demonstrated a direct connection between lattice geometry and emergent quantum states,” said Yi, an associate professor of physics and astronomy.

Experimental Techniques and Findings

The research team employed two advanced synchrotron techniques alongside theoretical modeling to investigate the presence of active standing-wave electron modes. They used angle-resolved photoemission spectroscopy (ARPES) to map electrons emitted under synchrotron light, revealing distinct signatures associated with compact molecular orbitals. Resonant inelastic X-ray scattering (RIXS) measured magnetic excitations linked to these electronic modes.

“The ARPES and RIXS results of our collaborative team give a consistent picture that flat bands here are not passive spectators but active participants in shaping the magnetic and electronic landscape,” said Si, the Harry C. and Olga K. Wiess Professor of Physics and Astronomy, “This is amazing to see given that, until now, we were only able to see such features in abstract theoretical models.”

Theoretical support was provided by analyzing the effect of strong correlations starting from a custom-built electronic lattice model, which replicated the observed features and guided the interpretation of results. Fang Xie, a Rice Academy Junior Fellow and co-first author, led that portion of the study. 

Obtaining such precise data required unusually large and pure crystals of CsCr₃Sb₅, synthesized using a refined method that produced samples 100 times larger than previous efforts, said Zehao Wang, a Rice graduate student and co-first author.

The work underscores the potential of interdisciplinary research across fields of study, said Yucheng Guo, a Rice graduate student and co-first author who led the ARPES work. 

“This work was possible due to the collaboration that consisted of materials design, synthesis, electron and magnetic spectroscopy characterization, and theory,” Guo said.

Reference: “Spin excitations and flat electronic bands in a Cr-based kagome superconductor” by Zehao Wang, Yucheng Guo, Hsiao-Yu Huang, Fang Xie, Yuefei Huang, Bin Gao, Ji Seop Oh, Han Wu, Jun Okamoto, Ganesha Channagowdra, Chien-Te Chen, Feng Ye, Xingye Lu, Zhaoyu Liu, Zheng Ren, Yuan Fang, Yiming Wang, Ananya Biswas, Yichen Zhang, Ziqin Yue, Cheng Hu, Chris Jozwiak, Aaron Bostwick, Eli Rotenberg, Makoto Hashimoto, Donghui Lu, Junichiro Kono, Jiun-Haw Chu, Boris I. Yakobson, Robert J. Birgeneau, Guang-Han Cao, Atsushi Fujimori, Di-Jing Huang, Qimiao Si, Ming Yi and Pengcheng Dai, 14 August 2025, Nature Communications.
DOI: 10.1038/s41467-025-62298-5

Funding: U.S. Department of Energy, Welch Foundation, Gordon and Betty Moore Foundation, Air Force Office of Scientific Research, U.S. National Science Foundation

Never miss a breakthrough: Join the SciTechDaily newsletter.