AS ABOVE, SO BELOW
Harnessing computational intelligence for 3D modeling of maize canopies
NANJING AGRICULTURAL UNIVERSITY THE ACADEMY OF SCIENCE
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THE COMPLETE METHODOLOGICAL PROCESS.
view moreCREDIT: PLANT PHENOMICS
Understanding the structure of crop canopies is essential for optimizing crop production as it significantly influences resource utilization efficiency, yield and stress resistance. While research has integrated canopy studies into various agricultural practices, the construction of accurate 3D models remains challenging due to complex spatial distributions and technological limitations. Current methods struggle to capture detailed morphological data due to issues such as resolution and cost. To address these issues, there is an emerging interest in applying Computational Intelligence (CI) techniques. These techniques have shown promise in various agricultural applications but haven’t yet been explored for constructing 3D models of maize canopies.
In March 2024, Plant Phenomics published a research article entitled by “Three-dimensional modelling of maize canopies based on computational intelligence”. This research aims to integrate CI into 3D plant canopy modeling, particularly focusing on overcoming the challenges of internal occlusion and resource competition among densely planted crops.
The study presents a computational intelligence-based 3D modeling method for maize canopies, focusing on visualizing and validating the structure of maize canopies across different planting densities and varieties. Using this method, 3D models for the JNK728 and JK968 maize varieties were constructed at densities of 3, 6, and 9×10^4 plants per hectare. The mothed demonstrated the method's ability to capture the effects of planting density on canopy structure, including increased shading and adjustments in leaf azimuth angles to optimize light capture. The models were validated and showed significant improvements in simulating the distribution of leaf azimuth angles, The R2 values indicated a high degree of consistency with measured data, especially after optimization through a reflective approach.
The study also validated the models' accuracy in representing canopy coverage, showing a correlation with actual canopy conditions and highlighting the models' limitations in capturing elements like fallen leaves and weeds. The distribution of leaf azimuth angles close to 90° increases with planting density, suggesting an adaptive response of maize leaves to environmental stress by aligning more perpendicular to the row direction. This trend was further validated through the construction of 3D models across a gradient of planting densities.
The computational process, though time-intensive, highlights the efficiency and potential of computational intelligence in 3D canopy modeling. The iterative optimization of sunlit leaf area ratios and the intelligent adjustment of 3D phytomers' azimuth angles reflect the application of swarm intelligence principles to crop canopy modeling. The study highlights the significance of precise crop canopy modeling to comprehend plant competition for light resources. It suggests further enhancements and future work to improve the models' accuracy and practicality by considering a broader range of environmental factors and incorporating more detailed phenotypic and growth information.
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References
Authors
Yandong Wu1,2† , Weiliang Wen2,3,4† , Shenghao Gu2,3, Guanmin Huang2,3,4, Chuanyu Wang2,3, Xianju Lu2,3,4, Pengliang Xiao1,2, Xinyu Guo2,3*, Linsheng Huang1*
† These authors contributed equally to the article.
Affiliations
1National Engineering Research Center for Agro-Ecological Big Data Analysis & Application, Anhui University, Hefei 230601, China.
2Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.
3Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China.
4Nongxin Science & Technology (Beijing) Co., Ltd, Beijing 100097, China
About Linsheng Huang
He is currently a Professor and the Deputy Director of the National Engineering Research Center for Agro-Ecological Big Data Analysis and Application, Anhui University. His research interests include quantitative remote sensing applications in crop diseases and insect pests.
JOURNAL
Plant Phenomics
METHOD OF RESEARCH
Experimental study
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
Three-dimensional modelling of maize canopies based on computational intelligence
Maize genes control little helpers in the soil
An international team of researchers discovers how microbes boost root growth
UNIVERSITY OF BONN
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PROF. DR. FRANK HOCHHOLDINGER (LEFT) AND DR. PENG YU (RIGHT) FROM THE CHAIR OF CROP FUNCTIONAL GENOMICS AT THE UNIVERSITY OF BONN
view moreCREDIT: PHOTO: VOLKER LANNERT/UNIVERSITY OF BONN
Tiny organisms such as bacteria and fungi help to promote the health and function of plant roots. It is commonly assumed that the composition of these microbes is dependent on the properties of the soil. However, an international team of researchers led by the University of Bonn has now discovered when studying different local varieties of maize that the genetic makeup of the plants also helps to influence which microorganisms cluster around the roots. The results, which have now been published in the prestigious journal Nature Plants, could help to breed future varieties of maize that are better suited to drought and limited nutrients.
In order to grow properly, plants take in water and nutrients through their roots. But they have the assistance of some tiny helpers: A layer of bacteria and fungi, just a few millimeters thick, can be found directly around the roots. “These microorganisms are essential for the health and fitness of the plants,” says Dr. Peng Yu, head of the junior research group “Root Functional Biology” at the Institute of Crop Science and Resource Conservation (INRES) at the University of Bonn. The microbes help with the absorption of water and nutrients and protect the plants against harmful organisms – similar to how the “microbiome” in the intestines of humans helps to determine whether we become ill or stay healthy.
The traditional view is that the composition of the microbiome – the totality of all microorganisms – is mainly determined by the properties of the soil. This includes things such as the type of soil and whether it is more acidic or alkaline. However, an international team of researchers led by the University of Bonn has now demonstrated in maize plants that the genetic makeup of the host plants has a significant influence on the composition of the root microbes.
“Our study also showed that the microbiome around the roots has a crucial influence on how resilient the maize plants are when faced with stressful conditions such as a nutrient deficits or lack of water,” says Prof. Dr. Frank Hochholdinger from the Crop Functional Genomics department in INRES at the University of Bonn. In view of global climate change and the limited supply of the nutrient phosphorous, resilience of these plants to drought and a lack of nutrients could play an even greater role in the future.
Adapting regional varieties of maize to environmental conditions
The various varieties of maize have very different genetic composition. Regional varieties have adapted themselves to very different environmental conditions depending on whether they are cultivated, for example, in cooler highland or the warmer lowland areas of South America. “The fact that farmers have continued to select those varieties of maize suited to the local climate over many centuries has led to very different genotypes that we were able to utilize for our study,” says Dr. Yu, who is head of an Emmy Noether junior research group funded by the German Research Foundation and also a member of the PhenoRob Cluster of Excellence and the transdisciplinary research area “Sustainable Futures” at the University of Bonn.
In cooperation with scientists from Southwest University in Chongqing (China), the researchers studied a total of 129 different varieties of maize. Some of these were cultivated under “normal” conditions while others experienced deficiencies in phosphorus, nitrogen, or water. Additionally, the team sequenced the DNA of the microbes from 3168 samples taken from the layer found directly around the roots that is just a few millimeters thick.
The role played by the genetic makeup of the roots became apparent in those plants grown under stressful conditions. Interestingly, the lack of nutrients and water had a significant influence on the composition of the microbes. Furthermore, the team discovered important characteristic differences in the microbiome between different varieties of maize under the same stressful conditions. “We were able to prove that certain maize genes are able to interact with certain bacteria,” says Dr. Yu to explain on the most important results. Using data on the growth conditions at the place of origin of a certain variety of maize and on its genetic composition, the researchers were even able to predict which key organisms would be found in the microbiome around the roots.
The bacterium Massilia promotes the growth of lateral roots
The results for bacteria of the genus Massilia especially stood out: “It was very noticeable that very few specimens of this microbe were found when there was a sufficient supply of nitrogen,” says Prof. Dr. Gabriel Schaaf from the Ecophysiology of Plant Nutrition department at INRES and member of the PhenoRob Cluster of Excellence. If there was a lack of nitrogen, however, lots of Massilia could be found clustering around the roots. The team then inoculated maize roots with this bacterium. The plants grew a lot more lateral roots as a result and were therefore able to significantly improve their uptake of nutrients and water.
But how do maize plants manage to harness the tiny Massilia bacterium for this type of root growth? Following further studies, the researchers discovered that the roots actually attracted the Massilia bacteria using flavones. This substance is one of many secondary metabolites in the plant and stimulates the growth of lateral roots with the aid of the bacteria. “However, this was dependent on whether the maize plant had a microtubule-binding gene,” says Dr. Peng Yu. If this gene was missing, the plant did not produce more lateral roots.
The varieties of maize with the missing gene come from a huge database of maize mutations that has been set up by the researchers headed by Dr. Caroline Marcon at INRES. This database helps researchers explain the functions of maize genes.
Maize varieties better adapted to drought and a lack of nutrients
The international team of researchers hopes that they will also be able to predict yield in the medium term. “We are carrying out basic research,” says Hochholdinger. “However, these results could act as the basis for cultivation of maize varieties better suited to drought and a lack of phosphorous by using genome and microbiome data.”
Participating institutes and funding:
Alongside various departments in the Institute of Crop Science and Resource Conservation (INRES) at the University of Bonn, the following institutions also participated in the research: Southwest University Chongqing (China), Leibniz Institute of Plant Genetics and Crop Plant Research, Pennsylvania State University (USA), Institute of Natural Resources and Agrobiology of Seville (Spain), University of Hohenheim, University of Nebraska-Lincoln (USA), Julius Kühn Institute in Braunschweig, Ghent University (Belgium), Center for Plant Systems Biology in Ghent, University of Amsterdam (Netherlands) and the Department of Food Microbiology at the University of Bonn. The study was funded by, amongst others, the German Research Foundation (DFG), including funds from the PhenoRob Cluster of Excellence.
Publication: Xiaoming He, Danning Wang, Yong Jiang, Meng Li, Manuel Delgado-Baquerizo, Chloee McLaughlin, Caroline Marcon, Li Guo, Marcel Baer, Yudelsy A.T. Moya, Nicolaus von Wirén, Marion Deichmann, Gabriel Schaaf, Hans-Peter Piepho, Zhikai Yang, Jinliang Yang, Bunlong Yim, Kornelia Smalla, Sofie Goormachtig, Franciska T. de Vries, Hubert Hüging, Mareike Baer, Ruairidh J. H. Sawers, Jochen C. Reif, Frank Hochholdinger, Xinping Chen, Peng Yu: Heritable microbiome variation is correlated with source environment in locally adapted maize varieties, Nature Plants, DOI: 10.1038/s41477-024-01654-7; Internet: https://www.nature.com/articles/s41477-024-01654-7
Video: https://youtu.be/VaYnX-ph9gg
Contact:
Dr. Peng Yu
Institute of Crop Science and Resource Conservation (INRES)
Crop Functional Genomics
University of Bonn
Tel. +49 228 73-60532
E-mail: yupeng@uni-bonn.de
Prof. Dr. Frank Hochholdinger
INRES – Crop Functional Genomics
University of Bonn
Tel. +49 228 73-60334 or -60331
E-mail: hochhold@uni-bonn.de
JOURNAL
Nature Plants
METHOD OF RESEARCH
Experimental study
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
Heritable microbiome variation is correlated with source environment in locally adapted maize varieties
ARTICLE PUBLICATION DATE
21-Mar-2024
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