Bringing genetics and biochemistry to crop modelling, and vice versa

Yin, Xinyou; Linden, C. Gerard van der; Struik, P.C.

doi:10.1016/j.eja.2018.02.005

Cited by 21 publications

(12 citation statements)

References 72 publications

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“…Crop model-based improved simulation techniques with response to environmental conditions have been developed for making effective and proper use of input resources [23]. Simulation models define the systematic processes related to crop growth and development and are useful tools to assess the impact of soil extrinsic factors (fertilization), variability of climatic conditions, and crop management practices [24,25] by providing credible predictions [26]. Typically, crop models consider the time span in which a specific growth stage takes place and initiate biomass of crop components, e.g., roots, leaves, stems, and yield attributes, as they change time to time, and similarly, changes in the nutrients content and soil moisture status.…”

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confidence: 99%

Modeling Water and Nitrogen Balance of Different Cropping Systems in the North China Plain

Leghari

Liang

et al. 2019

Agronomy

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The North China Plain (NCP) is experiencing serious groundwater level decline and groundwater nitrate contamination due to excessive water pumping and application of nitrogen (N) fertilizer. In this study, grain yield, water and N use efficiencies under different cropping systems including two harvests in 1 year (winter wheat-summer maize) based on farmer (2H1Y) FP and optimized practices (2H1Y) OPT , three harvests in 2 years (winter wheat-summer maize-spring maize, 3H2Y), and one harvest in 1 year (spring maize, 1H1Y) were evaluated using the water-heat-carbon-nitrogen simulator (WHCNS) model. The 2H1Y FP system was maintained with 100% irrigation and fertilizer, while crop water requirement and N demand for other cropping systems were optimized and managed by soil testing. In addition, a scenario analysis was also performed under the interaction of linearly increasing and decreasing N rates, and irrigation levels.Results showed that the model performed well with simulated soil water content, soil N concentration, leaf area index, dry matter, and grain yield. Statistically acceptable ranges of root mean square error, Nash-Sutcliffe model efficiency, index of agreement values close to 1, and strong correlation coefficients existed between simulated and observed values. We concluded that replacing the prevalent 2H1Y FP with 1H1Y would be ecofriendly at the cost of some grain yield decline. This cropping system had the highest average water use (2.1 kg m −3 ) and N use efficiencies (4.8 kg kg -1 ) on reduced water (56.64%) and N (81.36%) inputs than 2H1Y FP . Whereas 3H2Y showed insignificant results in terms of grain yield, and 2H1Y FP was unsustainable. The 2H1Y FP system consumed a total of 745 mm irrigation and 1100 kg N ha -1 in two years. When farming practices were optimized for two harvests in 1 year system (2H1Y) OPT , then grain yield improved and water (18.12%) plus N (61.82%) consumptions were minimized. There was an ample amount of N saved, but water conservation was still unsatisfactory. However, considering the results of scenario analyses, it is recommended that winter wheat would be cultivated at <200 mm irrigation by reducing one irrigation event.Since the 1970s, the annual use of the two-harvest cropping system greatly increased the total grain output. However, it has also caused severe groundwater decline [7,8], because both crops generally have high water requirements to complete their life cycle [9,10]. Crop water requirement does not meet the balance between groundwater recharge through rain and evapotranspiration (ET) loss from plant and soil [11]. An estimated amount of more than 450 mm yr −1 irrigation water is required to maintain high crop yield under the conventional double cropping system [12], which dominatingly depends on pumping of groundwater, and there is no access to irrigation from the river source. Thus, the groundwater is almost the only source of irrigation [13]. In the last 20 years, sustained water pumping has adversely affected aquifers. Consequently, the groundwater leve...

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confidence: 99%

Modeling Water and Nitrogen Balance of Different Cropping Systems in the North China Plain

Leghari

Liang

et al. 2019

Agronomy

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“…For the sunflower crop, while low-throughput phenotyping enabled the link between crop physiology and modeling, we showed in this study that the automation allowed us to use functional genomics tool to better study the genetic basis of complex traits (Yin et al, 2018). While other phenotyping platforms are focused on this goal, such as the PHENOARCH platform (Cabrera-Bosquet et al, 2016) recently used by Chen et al (2018) to estimate genotype-specific radiation use efficiency in complex canopies through reverse modeling; platforms operating in outdoor conditions are not frequent (Araus et al, 2018).…”

Section: Discussionmentioning

confidence: 95%

Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling

et al. 2019

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Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant water status and phenotypes the leaf or whole-plant morphology. From these measurements, we can compute more complex traits, such as leaf expansion (LE) or transpiration rate (TR) in response to water deficit. Here, we illustrate the capabilities of the platform with two practical cases in sunflower (Helianthus annuus): a genetic and genomic study of the response of yield-related traits to drought, and a modeling study using measured parameters as inputs for a crop simulation. For the genetic study, classical measurements of thousand-kernel weight (TKW) were performed on a biparental population under automatically managed drought stress and control conditions. These data were used for an association study, which identified five genetic markers of the TKW drought response. A complementary transcriptomic analysis identified candidate genes associated with these markers that were differentially expressed in the parental backgrounds in drought conditions. For the simulation study, we used a crop simulation model to predict the impact on crop yield of two traits measured on the platform (LE and TR) for a large number of environments. We conducted simulations in 42 contrasting locations across Europe using 21 years of climate data. We defined the pattern of abiotic stresses occurring at the continental scale and identified ideotypes (i.e., genotypes with specific trait values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can assist the identification of the genetic architecture controlling complex response traits and facilitate the estimation of ecophysiological model parameters to define ideotypes adapted to different environmental conditions.

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“…Combining the results with crop models will improve the output to levels 4 and 5 (quantitative knowledge) with the inclusion of other data types such as solar radiation, crop water and nutrient use efficiency, etc. Such quantitative modelling efforts can be carried out with either experimental data from known crop genotypes/varieties or landraces [43] or with simulations of suitability for accessions collected in similar pedoclimatic conditions using globally available datasets [37,44]. Finally putting all of these insights together in open access software tools can help with rapid delineation of alternative cropping options.…”

Section: Combining With Traditional Land System Modelsmentioning

confidence: 99%

A Land Evaluation Framework for Agricultural Diversification

Jahanshiri

Nizar²,

Suhairi³

et al. 2020

Sustainability

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Shortlisting ecologically adaptable plant species can be a starting point for agricultural diversification projects. We propose a rapid assessment framework based on an ecological model that can accelerate the evaluation of options for sustainable crop diversification. To test the new model, expert-defined and widely available crop requirement data were combined with more than 100,000 occurrence data for 40 crops of different types (cereals, legumes, vegetables, fruits, and tubers/roots). Soil pH, texture, and depth to bedrock data were obtained and harmonised based on the optimal rooting depths of each crop. Global baseline temperature and rainfall data were used to extract averages at each location. To evaluate the ability of the method to capture intraspecies variation, a test was performed using more than 1000 accession records of bambara groundnut (Vigna subterranea (L.) Verdc.) as an exemplar underutilised crop. Results showed that a suitability index based on soil pH and an index that combines the thermal suitability moderated by the soil pH, texture, and depth suitability have the potential to predict crop adaptability. We show that the proposed method can be combined with traditional land use and crop models to evaluate diversification options for sustainable land and agrobiodiversity resources management.

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Bringing genetics and biochemistry to crop modelling, and vice versa

Cited by 21 publications

References 72 publications

Modeling Water and Nitrogen Balance of Different Cropping Systems in the North China Plain

Modeling Water and Nitrogen Balance of Different Cropping Systems in the North China Plain

Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling

A Land Evaluation Framework for Agricultural Diversification

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