Fundamentals of rice crop science

Roots and Nitrogen in Cropping Systems of the Semi-Arid Tropics, (半乾燥熱帯の作付け体系における根と窒素の動態), 伊藤 治・C. ジョハンセン・J.J.アドギャンフィ片山勝之・T.J.レゴ・J.V.D.K.クマラオ編著, JIRCAS International Agriculture Series No. 3(Tsukuba), B5判, 691pp., 1996年

Plant-derived protein biostimulants exhibit hormone-like activities promoting plant growth and yield, yet detailed investigations on hormonal function have remained limited. This study was conducted to investigate the effects of vegetal-derived-biostimulant on morphological and metabolic changes in cuttings of three herbaceous species demonstrating different rooting ability, basil (Ocimum basilicum L.), tomato (Solanum lycopersicum L.), and chrysanthemum (Chrysanthemum indicum L.), in comparison to auxin. Unrooted cuttings were applied with or without biostimulant (100, 1000, 5000, and 10,000 mg L−1) or auxin [1% indole-3-butyric acid (IBA) plus 0.5% 1-naphthaleneacetic acid (NAA); 100, 200, 300, and 500 mg L−1] as a basal quick-dip, stuck into inert media, and evaluated at 20 days after placement under intermittent mist. Both compounds increased adventitious rooting in all cuttings. Biostimulant required a significantly higher threshold for a series of adventitious rooting responses than auxin, and the maximum effectiveness was achieved at 5000 mg L−1 for biostimulant and 100, 200, and 300 mg L−1 for auxin in basil, tomato, and chrysanthemum, respectively. Adventitious rooting responses (dry mass and length) to biostimulant showed a gradual logarithmic rise as a function of increasing dosages, which was not in agreement with biphasic dose-response of auxin. Biostimulant significantly increased or tended to increase fine roots in all tested cuttings, which was not consistent with auxin. Relatively high levels of endogenous brassinosteroids (BRs) were present in non-treated cuttings of basil, tomato, and chrysanthemum in decreasing order. Both compounds had no effects or concomitantly increased or decreased BR levels in plant tissues, with fewer effects on basil and tomato, containing high BR levels, but more prominent effects on chrysanthemum, containing relatively low BR levels. Contrasting effects of biostimulant and auxin were found in antioxidant activities, which were promoted by biostimulant but inhibited by auxin either in roots or shoots. These results indicate that the hormonal effects of vegetal-derived biostimulant are primarily exerted by BR-mediated processes while involving interaction with auxin. Both the biostimulant-derived BRs and auxin were suggested to modulate endogenous BR pool via overlapping and interdependent regulatory functions, inducing morphological and metabolic changes during adventitious rooting of cuttings in a plant species-specific manner.

https://www.mdpi.com/2073-4395/9/2/74/pdf

Vegetal-Derived Biostimulant Enhances Adventitious Rooting in Cuttings of Basil, Tomato, and Chrysanthemum via Brassinosteroid-Mediated Processes

The efficient use of resources such as water and nutrients by plants is increasingly important as the world population food demand continues to grow With the increased production of lentil in the temperate zones of North America, improvement in yield needs to be maintained The use of wild lentil genotypes as sources of genetic diversity for introgression into cultivated lentil is an important breeding strategy, but little is known about their root systems We evaluated the root systems of five wild lentil species and Lens culinaris under fully watered conditions Plants were grown in 60 cm tubes containing equal volumes of soil collected from the reconstructed A, B, and C horizons Significant differences were observed for root traits and fine root distribution between and within species and the proportion of root biomass partitioned into each soil layer was unique for each genotype We also observed variability in nodule number and nodule shape within and between genotypes Some genotypes more efficiently used water for either biomass or seed production The allocation of resources to seed production also varied between genotypes These observations could have impact on the design of future lentil breeding in the context of strategies for managing changes in rainfall amount and distribution for lentil production ecosystems

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Root Traits, Nodulation and Root Distribution in Soil for Five Wild Lentil Species and Lens culinaris (Medik.) Grown under Well-Watered Conditions.

Root distribution in the soil determines plants' nutrient and water uptake capacity. Therefore, root distribution is one of the most important factors in crop production. The trench profile method is used to observe the root distribution underground by making a rectangular hole close to the crop, providing informative images of the root distribution compared to other root phenotyping methods. However, much effort is required to segment the root area for quantification. In this study, we present a promising approach employing a convolutional neural network for root segmentation in trench profile images. We defined two parameters, Depth50 and Width50, representing the vertical and horizontal centroid of root distribution, respectively. Quantified parameters for root distribution in rice (Oryza sativa L.) predicted by the trained model were highly correlated with parameters calculated by manual tracing. These results indicated that this approach is useful for rapid quantification of the root distribution from the trench profile images. Using the trained model, we quantified the root distribution parameters among 60 rice accessions, revealing the phenotypic diversity of root distributions. We conclude that employing the trench profile method and a convolutional neural network is reliable for root phenotyping and it will furthermore facilitate the study of crop roots in the field.

/pdf/a-deep-learning-based-phenotypic-analysis-of-rice-root-2jpqja8myd.pdf

A Deep Learning-Based Phenotypic Analysis of Rice Root Distribution from Field Images.

Quantitative study of root morphological characteristics of plants is helpful for understanding the relationships between their morphology and function. However, few studies and little detailed and accurate information of root characteristics were reported in fine-rooted plants like rice (Oryza sativa L.). The aims of this study were to quantitatively classify fine lateral roots (FLRs), thick lateral roots (TLRs), and nodal roots (NRs) and analyze their dynamics of mean diameter (MD), lengths and surface area percentage with growth stages in rice plant. Pot experiments were carried out during three years with three rice cultivars, three nitrogen (N) rates and three water regimes. In cultivar experiment, among the three cultivars, root length of ‘Yangdao 6’ was longest, while the MD of its FLR was the smallest, and the mean diameters for TLR and NR were the largest, the surface area percentage (SAP) of TLRs (SAPT) was the highest, indicating that Yangdao 6 has better nitrogen and water uptake ability. High N rate increased the length of different types of roots and increased the MD of lateral roots, decreased the SAP of FLRs (SAPF) and TLRs, but increased the SAP of NRs (SAPN). Moderate decrease of water supply increased root length and diameter, water stress increased the SAPF and SAPT, but decreased SAPN. The quantitative results indicate that rice plant tends to increase lateral roots to get more surface area for nitrogen and water uptake when available assimilates are limiting under nitrogen and water stress environments.

Quantitative Classification of Rice (Oryza sativa L.) Root Length and Diameter Using Image Analysis.

Modeling leaf color dynamics in rice (Oryza sativa L.) is an important task for realizing virtual and digital plant growth. This study was undertaken to analyze the dynamics of leaf color changes at different leaf positions on main stems and tillers under different growing conditions, and to build a dynamic simulation model on leaf color changes in rice plant in relation to growing degree-days (GDD). Time-course observations were made on leaf color (in SPAD value) changes at different leaf positions of stem and tillers under different nitrogen rates and water regimes with four rice cultivars. Leaf color changes in SPAD could be described in three phases. The first phase during leaf elongation period was based on the exponential relationship of leaf color to cumulative GDD; the second phase during leaf function period was represented with a relative stable SPAD; the third phase during leaf senescence period was described in a quadratic equation between SPAD and GDD. In addition, the effects of nitrogen and water conditions on leaf color were quantified through the effectiveness values of leaf nitrogen concentration and water content in relation to SPAD. Then, the RGB (red, green, and blue) values were further predicted from the changing SPAD during leaf development. The model was validated with the independent field experiment data involving different rice cultivars and nitrogen rates. The average root mean square errors (RMSE) between the simulated and observed SPAD values at different leaf positions were 2.58, 3.69 and 3.82, respectively, for three leaf color phases on main stem; 4.65, 4.39, 3.51 and 4.25, respectively, for four individual tillers; and 2.98 and 3.25, respectively, for SPAD and R, G values in rice. The results indicate that the present model has a good performance in predicting leaf color changes at different leaf positions in rice under various growth conditions, and thus lays a foundation for further constructing digital and visual rice growth system.

Dongxiang Gu

Papers

Quantitative Classification of Rice (Oryza sativa L.) Root Length and Diameter Using Image Analysis.

Modeling leaf color dynamic in rice plant based on spad value