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Zhang Y, Henke M, Li Y, Xu D, Liu A, Liu X, Li T. Analyzing the Impact of Greenhouse Planting Strategy and Plant Architecture on Tomato Plant Physiology and Estimated Dry Matter. FRONTIERS IN PLANT SCIENCE 2022; 13:828252. [PMID: 35242156 PMCID: PMC8885523 DOI: 10.3389/fpls.2022.828252] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 01/13/2022] [Indexed: 05/17/2023]
Abstract
Determine the level of significance of planting strategy and plant architecture and how they affect plant physiology and dry matter accumulation within greenhouses is essential to actual greenhouse plant management and breeding. We thus analyzed four planting strategies (plant spacing, furrow distance, row orientation, planting pattern) and eight different plant architectural traits (internode length, leaf azimuth angle, leaf elevation angle, leaf length, leaflet curve, leaflet elevation, leaflet number/area ratio, leaflet length/width ratio) with the same plant leaf area using a formerly developed functional-structural model for a Chinese Liaoshen-solar greenhouse and tomato plant, which used to simulate the plant physiology of light interception, temperature, stomatal conductance, photosynthesis, and dry matter. Our study led to the conclusion that the planting strategies have a more significant impact overall on plant radiation, temperature, photosynthesis, and dry matter compared to plant architecture changes. According to our findings, increasing the plant spacing will have the most significant impact to increase light interception. E-W orientation has better total light interception but yet weaker light uniformity. Changes in planting patterns have limited influence on the overall canopy physiology. Increasing the plant leaflet area by leaflet N/A ratio from what we could observe for a rose the total dry matter by 6.6%, which is significantly better than all the other plant architecture traits. An ideal tomato plant architecture which combined all the above optimal architectural traits was also designed to provide guidance on phenotypic traits selection of breeding process. The combined analysis approach described herein established the causal relationship between investigated traits, which could directly apply to provide management and breeding insights on other plant species with different solar greenhouse structures.
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Affiliation(s)
- Yue Zhang
- College of Horticulture, Shenyang Agricultural University, Shenyang, China
- Key Laboratory of Protected Horticulture, Ministry of Education, Shenyang, China
- National & Local Joint Engineering Research Center of Northern Horticultural Facilities Design & Application Technology (Liaoning), Shenyang, China
| | - Michael Henke
- Plant Sciences Core Facility, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czechia
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Stadt Seeland, Germany
| | - Yiming Li
- Key Laboratory of Protected Horticulture, Ministry of Education, Shenyang, China
- National & Local Joint Engineering Research Center of Northern Horticultural Facilities Design & Application Technology (Liaoning), Shenyang, China
- College of Engineering, Shenyang Agricultural University, Shenyang, China
| | - Demin Xu
- College of Horticulture, Shenyang Agricultural University, Shenyang, China
- Key Laboratory of Protected Horticulture, Ministry of Education, Shenyang, China
- National & Local Joint Engineering Research Center of Northern Horticultural Facilities Design & Application Technology (Liaoning), Shenyang, China
| | - Anhua Liu
- College of Horticulture, Shenyang Agricultural University, Shenyang, China
- Key Laboratory of Protected Horticulture, Ministry of Education, Shenyang, China
- National & Local Joint Engineering Research Center of Northern Horticultural Facilities Design & Application Technology (Liaoning), Shenyang, China
| | - Xingan Liu
- College of Horticulture, Shenyang Agricultural University, Shenyang, China
- Key Laboratory of Protected Horticulture, Ministry of Education, Shenyang, China
- National & Local Joint Engineering Research Center of Northern Horticultural Facilities Design & Application Technology (Liaoning), Shenyang, China
| | - Tianlai Li
- College of Horticulture, Shenyang Agricultural University, Shenyang, China
- Key Laboratory of Protected Horticulture, Ministry of Education, Shenyang, China
- National & Local Joint Engineering Research Center of Northern Horticultural Facilities Design & Application Technology (Liaoning), Shenyang, China
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Radiative Transfer Image Simulation Using L-System Modeled Strawberry Canopies. REMOTE SENSING 2022. [DOI: 10.3390/rs14030548] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/07/2022]
Abstract
The image-based modeling and simulation of plant growth have numerous and diverse applications. In this study, we used image-based and manual field measurements to develop and validate a methodology to simulate strawberry (Fragaria × ananassa Duch.) plant canopies throughout the Florida strawberry growing season. The simulated plants were used to create a synthetic image using radiative transfer modeling. Observed canopy properties were incorporated into an L-system simulator, and a series of strawberry canopies corresponding to specific weekly observation dates were created. The simulated canopies were compared visually with actual plant images and quantitatively with in-situ leaf area throughout the strawberry season. A simple regression model with L-system-derived and in-situ total leaf areas had an Adj R2 value of 0.78. The L-system simulated canopies were used to derive information needed for image simulation, such as leaf area and leaf angle distribution. Spectral and plant canopy information were used to create synthetic high spatial resolution multispectral images using the Discrete Anisotropic Radiative Transfer (DART) software. Vegetation spectral indices were extracted from the simulated image and used to develop multiple regression models of in-situ biophysical parameters (leaf area and dry biomass), achieving Adj R2 values of 0.63 and 0.50, respectively. The Normalized Difference Vegetation Index (NDVI) and the Red Edge Simple Ratio (SRre) vegetation indices, which utilize the red, red edge, and near infrared bands of the spectrum, were identified as statistically significant variables (p < 0.10). This study showed that both geometric (canopy seize metrics) and spectral variables were successful in modeling in-situ biomass and leaf area. Combining the geometric and spectral variables, however, only slightly improved the prediction model. These results show the feasibility of simulating strawberry canopies and images with inherent geometrical, topological, and spectral properties of real strawberry plants. The simulated canopies and images can be used in applications beyond creating realistic computer graphics for quantitative applications requiring the depiction of vegetation biological processes, such as stress modeling and remote sensing mission planning.
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O’Sullivan H, Raumonen P, Kaitaniemi P, Perttunen J, Sievänen R. Integrating terrestrial laser scanning with functional-structural plant models to investigate ecological and evolutionary processes of forest communities. ANNALS OF BOTANY 2021; 128:663-684. [PMID: 34610091 PMCID: PMC8557364 DOI: 10.1093/aob/mcab120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 09/13/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Woody plants (trees and shrubs) play an important role in terrestrial ecosystems, but their size and longevity make them difficult subjects for traditional experiments. In the last 20 years functional-structural plant models (FSPMs) have evolved: they consider the interplay between plant modular structure, the immediate environment and internal functioning. However, computational constraints and data deficiency have long been limiting factors in a broader application of FSPMs, particularly at the scale of forest communities. Recently, terrestrial laser scanning (TLS), has emerged as an invaluable tool for capturing the 3-D structure of forest communities, thus opening up exciting opportunities to explore and predict forest dynamics with FSPMs. SCOPE The potential synergies between TLS-derived data and FSPMs have yet to be fully explored. Here, we summarize recent developments in FSPM and TLS research, with a specific focus on woody plants. We then evaluate the emerging opportunities for applying FSPMs in an ecological and evolutionary context, in light of TLS-derived data, with particular consideration of the challenges posed by scaling up from individual trees to whole forests. Finally, we propose guidelines for incorporating TLS data into the FSPM workflow to encourage overlap of practice amongst researchers. CONCLUSIONS We conclude that TLS is a feasible tool to help shift FSPMs from an individual-level modelling technique to a community-level one. The ability to scan multiple trees, of multiple species, in a short amount of time, is paramount to gathering the detailed structural information required for parameterizing FSPMs for forest communities. Conventional techniques, such as repeated manual forest surveys, have their limitations in explaining the driving mechanisms behind observed patterns in 3-D forest structure and dynamics. Therefore, other techniques are valuable to explore how forests might respond to environmental change. A robust synthesis between TLS and FSPMs provides the opportunity to virtually explore the spatial and temporal dynamics of forest communities.
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Affiliation(s)
- Hannah O’Sullivan
- Department of Life Sciences, Imperial College London, Silwood Park, Ascot, Berkshire, SL5 7PY, UK
- Royal Botanic Gardens, Kew, Richmond, UK
| | - Pasi Raumonen
- Mathematics, Tampere University, Korkeakoulunkatu 7, FI-33720 Tampere, Finland
| | - Pekka Kaitaniemi
- Hyytiälä Forestry Field Station, Faculty of Agriculture and Forestry, University of Helsinki, Hyytiäläntie 124, FI-35500 Korkeakoski, Finland
| | - Jari Perttunen
- Natural Resources Institute Finland, Latokartanontie 9, 00790 Helsinki, Finland
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Louarn G, Song Y. Two decades of functional-structural plant modelling: now addressing fundamental questions in systems biology and predictive ecology. ANNALS OF BOTANY 2020; 126:501-509. [PMID: 32725187 PMCID: PMC7489058 DOI: 10.1093/aob/mcaa143] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 07/25/2020] [Indexed: 05/16/2023]
Abstract
BACKGROUND Functional-structural plant models (FSPMs) explore and integrate relationships between a plant's structure and processes that underlie its growth and development. In the last 20 years, scientists interested in functional-structural plant modelling have expanded greatly the range of topics covered and now handle dynamical models of growth and development occurring from the microscopic scale, and involving cell division in plant meristems, to the macroscopic scales of whole plants and plant communities. SCOPE The FSPM approach occupies a central position in plant science; it is at the crossroads of fundamental questions in systems biology and predictive ecology. This special issue of Annals of Botany features selected papers on critical areas covered by FSPMs and examples of comprehensive models that are used to solve theoretical and applied questions, ranging from developmental biology to plant phenotyping and management of plants for agronomic purposes. Altogether, they offer an opportunity to assess the progress, gaps and bottlenecks along the research path originally foreseen for FSPMs two decades ago. This review also allows discussion of current challenges of FSPMs regarding (1) integration of multidisciplinary knowledge, (2) methods for handling complex models, (3) standards to achieve interoperability and greater genericity and (4) understanding of plant functioning across scales. CONCLUSIONS This approach has demonstrated considerable progress, but has yet to reach its full potential in terms of integration and heuristic knowledge production. The research agenda of functional-structural plant modellers in the coming years should place a greater emphasis on explaining robust emergent patterns, and on the causes of possible deviation from it. Modelling such patterns could indeed fuel both generic integration across scales and transdisciplinary transfer. In particular, it could be beneficial to emergent fields of research such as model-assisted phenotyping and predictive ecology in managed ecosystems.
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Affiliation(s)
| | - Youhong Song
- Anhui Agricultural University, School of Agronomy, Hefei, Anhui Province, PR China
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