Biology subjects

Merckx, R.

Publications and source records attributed to Merckx, R..

4 recordsLinked to original sources

bioRxiv2020

Phenotyping Root Architecture of Soil-Grown Rice: A Robust Protocol Combining Manual Practices with Image-based Analyses.

BackgroundBreeding towards resilient rice varieties is often constrained by the limited data on root system architecture obtained from relevant agricultural environments. Knowledge on the genotypic differences and responses of root architecture to environmental factors is limited due the difficulty of analysing soil-grown rice roots. An improved method using imaging is thus needed, but the existing methods were never proven successful for rice. Here, we aimed to evaluate and improve a higher throughput method of image-based root phenotyping for rice grown under field conditions. Rice root systems from seven experiments were phenotyped based on the "shovelomics" method of root system excavation followed by manual root phenotyping and digital root analysis after root imaging. Analyzed traits were compared between manual and image-based root phenotyping systems using Spearman rank correlations to evaluate whether both methods similarly rank the phenotypes. For each trait, the relative phenotypic variation was calculated. A principal component analysis was then conducted to assess patterns in root architectural variation. ResultsSeveral manually collected and image-based root traits were identified as having a high potential of differentiating among contrasting phenotypes, while other traits are found to be inaccurate and thus unreliable for rice. The image-based traits projected area, root tip thickness, stem diameter, and root system depth successfully replace the manual determination of root characteristics, however attention should be paid to the lower accuracy of the image-based methodology, especially when working with older and larger root systems. ConclusionsThe challenges and opportunities of rice root phenotyping in field conditions are discussed for both methods. We therefore propose an integrated protocol adjusted to the complexity of the rice root structure combining image analysis in a water bath and the manual scoring of three traits (i.e. lateral density, secondary branching degree, and nodal root thickness at the root base). The proposed methodology ensures higher throughput and enhanced accuracy during root phenotyping of soil grown rice in fields or pots compared to manual scoring only, it is cheap to develop and operate, it is valid in remote environments, and it enables fast data extraction.

developmental biology↗

bioRxiv2020

Farm yard manure enhances phosphate fertilizer use efficiency in different upland rice genotypes through mitigating aluminium toxicity

Upland rice production on weathered soils is often constrained by phosphorus (P) deficiency and soil acidity. Farmyard manure application (FYM) can sharply enhance yields and agronomic P fertilizer (TSP) efficiency. We tested the hypothesis that rice genotypes differ in the extent of using organic P and offering distinct benefits under TSP-FYM combinations. Multiple field trials were conducted in the uplands of Madagascar, with factorial combinations of six genotypes, FYM, and TSP applications, with blanket N&K additions. Rice grain yields reached 6 t ha-1 after three years of TSP+FYM application, were lower when FYM or TSP were used separately, while crops failed under zero P input. Genotypic differences were inferior to the large treatment effects. Application of FYM increased soil pH and CaCl2-extractable P while decreasing CaCl2-extractable aluminium. An additional liming trial indicated that beneficial effects of FYM over TSP relate to liming effects. Genotypic ranking of yields and agronomic efficiency was inconsistent, without superior genotypes under FYM versus TSP. However, Chomrong Dhan and FOFIFA 172 showed superior yields under TSP+FYM. The FYM application lowers aluminium toxicity which overrules potential effects of organic P supply. Aluminium tolerance should be included when developing rice genotypes for low P tolerance in weathered soils.

plant biology↗

bioRxiv2020

Water and phosphorus uptake by upland rice root systems unraveled under multiple scenarios: linking a 3D soil-root model and data

Background and aimsUpland rice is often grown where water and phosphorus (P) are limited and these two factors interact on P bioavailability. To better understand this interaction, mechanistic models representing small-scale nutrient gradients and water dynamics in the rhizosphere of full-grown root systems are needed. MethodsRice was grown in large columns using a P-deficient soil at three different P supplies in the topsoil (deficient, suboptimal, non-limiting) in combination with two water regimes (field capacity versus drying periods). Root architectural parameters and P uptake were determined. Using a multiscale model of water and nutrient uptake, in-silico experiments were conducted by mimicking similar P and water treatments. First, 3D root systems were reconstructed by calibrating an architecure model with observed phenological root data, such as nodal root number, lateral types, interbranch distance, root diameters, and root biomass allocation along depth. Secondly, the multiscale model was informed with these 3D root architectures and the actual transpiration rates. Finally, water and P uptake were simulated. Key resultsThe plant P uptake increased over threefold by increasing P and water supply, and drying periods reduced P uptake at high but not at low P supply. Root architecture was significantly affected by the treatments. Without calibration, simulation results adequately predicted P uptake, including the different effects of drying periods on P uptake at different P levels. However, P uptake was underestimated under P deficiency, a process likely related to an underestimated affinity of P uptake transporters in the roots. Both types of laterals (i.e. S- and L-type) are shown to be highly important for both water and P uptake, and the relative contribution of each type depend on both soil P availability and water dynamics. Key drivers in P uptake are growing root tips and the distribution of laterals. ConclusionsThis model-data integration demonstrates how multiple co-occurring single root phene responses to environmental stressors contribute to the development of a more efficient root system. Further model improvements such as the use of Michaelis constants from buffered systems and the inclusion of mycorrhizal infections and exudates are proposed.

developmental biology↗

bioRxiv2019

Balanced nutrient requirements for maize in the Northern Nigerian Savanna: Parameterization and validation of QUEFTS model

Establishing balanced nutrient requirements for maize (Zea mays L.) in the Northern Nigerian Savanna is paramount to develop site-specific fertilizer recommendations to increase maize yield, profits of farmers and avoid negative environmental impacts of fertilizer use. The model QUEFTS (QUantitative Evaluation of Fertility of Tropical Soils) was used to estimate balanced nitrogen (N), phosphorus (P) and potassium (K) requirements for maize production in the Northern Nigerian Savanna. Data from on-farm nutrient omission trials conducted in 2015 and 2016 rainy seasons in two agro-ecological zones in the Northern Nigerian Savanna (i.e. Northern Guinea Savanna \"NGS\" and Sudan Savanna \"SS\") were used to parameterize and validate the QUEFTS model. The relations between indigenous soil N, P, and K supply and soil properties were not well described with the QUEFTS default equations and consequently new and better fitting equations were derived. The average fertilizer recovery fractions of N, P and K in the NGS were generally comparable with the QUEFTS default values, but lower recovery fractions of these nutrients were observed in the SS. The parameters of maximum accumulation (a) and dilution (d) in kg grain per kg nutrient for the QUEFTS model obtained were respectively 35 and 79 for N, 200 and 527 for P and 25 and 117 for K in the NGS zone and 32 and 79 for N, 164 and 528 for P and 24 and 136 for K in the SS zone. The model predicted a linear relationship between grain yield and above-ground nutrient uptake until yield reached about 50 to 60% of the yield potential. When the yield target reached 60% of the potential yield (i.e. 6.0 tonnes per hectare), the model showed above-ground nutrient uptake of 19.4, 3.3 and 23.0 kg N, P, and K, respectively, per one tonne of maize grain in the NGS, and 17.3, 5.3 and 26.2 kg N, P and K, respectively, per one tonne of maize grain in the SS. These results suggest an average NPK ratio in the plant dry matter of about 5.9:1:7.0 for maize in the NGS and 3.3:1:4.9 for maize in the SS. There was a close agreement between observed and parameterized QUEFTS predicted yields across the two agro-ecological zones (R2 = 0.70 for the NGS and 0.86 for the SS). We concluded that the QUEFTS model can be used for balanced nutrient requirement estimations and development of site-specific fertilizer recommendations for maize intensification in the Northern Nigerian Savanna.

bioengineering↗