Rice Nitrogen Research Articles

The mass water content of paddy soil after harvest is strongly associated with the accumulation of organic matter as the source of available nitrogen

ABSTRACT Paddy soils are the dominant source of nitrogen for rice via mineralization, and knowledge about the available nitrogen (AN) in paddy soil is important for rice cultivation. Although the relationship between AN and soil physicochemical parameters has been studied, no systematic studies of the relationships between AN and the soil moisture content of various soil types in Japan have been studied. Therefore, we examined the impacts of soil types and treatment of organic matter application or paddy–upland rotation on these relationships. We sampled topsoils from 30 paddy fields throughout Japan. We compared the relationships between AN and soil physicochemical properties, such as total nitrogen (TN), cation exchange capacity, soil water-holding capacity (WHC), mass water content after harvest (MWH), and water content after harvest (WCH). The scatter diagram revealed that AN and either MWH or WCH (p < 0.01) had the highest positive linear correlation coefficient; the pattern became clearer after separating Andosols and non-Andosols. We analyzed the relationship between AN and either TN or MWH in 100 topsoils, including soils from treatment plots with successive organic matter application or paddy-upland rotation. A significantly positive correlation between AN and TN was observed, although the regression slopes for volcanic or non-volcanic soils differed. The decrease in AN due to frequent paddy–upland rotation was greater than that for TN. On the other hand, a highly positive correlation between AN and MWH was observed, and the coefficient of determination was higher than that for AN and TN. TN and the WHC increased when the accumulation of organic matter in paddy soil was greater. As there was a positive correlation between WHC and MWH, a positive correlation was also observed between AN and MWH. Additionally, we investigated year-to-year variation in MWH using topsoil samples collected before autumn tillage, for 3–5 consecutive years in 24 plots, for various soil types throughout Japan. In order to eliminate the effects of precipitation and to minimize the fluctuation of MWH in paddy topsoil, it was desirable to collect topsoil samples within 24–96 hours of the last precipitation of 1 mm h−1 or more, for the measurement of moisture content.

&lt;sup&gt;15&lt;/sup&gt;N Tracer-based Analysis on Nitrogen Utilization Laws of Rice Under Different Irrigation Modes

In order to promote the efficient and coordinated utilization of water and nitrogen in rice, the&nbsp; 15 N missing technology experiment was adopted to study the effects of nitrogen application rate (N 0 , N 160 , N 200 , N 240 ) and irrigation mode (Wet-dry alternation, conventional irrigation) on nitrogen absorption, transport, residue, loss and nitrogen utilization of super rice. The results showed that with the increase of nitrogen application rate, the accumulation of fertilizer nitrogen and total nitrogen in rice plants at different growth stages, and the accumulation of nitrogen in various organs at mature stage increased significantly, and the accumulation of nitrogen per panicle at mature stage was the highest, reaching 67.20%~69.02%. The transport amount of nitrogen from different sources in different vegetative organs of rice plants increased with the increase of nitrogen application rate, and the comparison of nitrogen transport amount in organs was as follows: leaf &gt; stem &gt; root; After full heading, the accumulation of nitrogen from different sources and its contribution rate to grain nitrogen per spike increased with the increase of nitrogen application rate, but with the increase of nitrogen application rate, the residual amount of soil fertilizer nitrogen increased significantly, the residual rate showed a downward trend, and the nitrogen loss rate increased significantly. Dry-wet alternate irrigation treatment can increase nitrogen accumulation in different organs of rice in different periods, improve nitrogen use efficiency and rice yield to a certain extent. This study summarized the laws of nitrogen absorption, utilization, residue and loss of rice under different irrigation conditions and different nitrogen application conditions, which provided a theoretical basis for efficient cultivation of rice.

Leaf colour chart: An incredible tool for field-specific management of fertilizer nitrogen in cereals in South Asia

Leaf colour chart (LCC) as a tool for field-specific management of fertilizer nitrogen (N) in rice was introduced on a commercial scale in the last decade of 20th century. During last two decades, its use has also been extended to wheat and maize. Many studies have been carried out on LCC-based N management in South Asian countries where farmers apply substantial amount of fertilizer N to cereal crops, but do not strictly follow even the regional blanket fertilizer N recommendations. LCC-based fertilizer N management in cereals leads to improvement in N use efficiency over that observed with blanket recommendation. It is an attempt to review the development of LCCs in South Asia, the modes in which LCC can be used - adjustable time and N dose in real time, fixed time adjustable N dose, and fixed N dose adjustable time, and the results of studies on field-specific LCC-based fertilizer N management carried out on rice, wheat, and maize in different parts of South Asia. By applying fertilizer N as guided by LCC, improvement in N use efficiency is observed either through reduced total amount of applied N, increased yield, or both. Performance of LCC-based site-specific N management at on-farm locations has also been reviewed. Studies providing direct evidence of reduced losses of N to environment due to LCC guided fertilizer N management rather than regional blanket recommendations suggest that LCC is going to be an incredible tool to enhance food security and minimize N related environmental degradation in South Asia.

Effects of Nitrogen-Loaded Biochar on Rice Growth, Nitrogen Uptake and Nitrogen Concentration Changes in Surface Water Under Alternate Wet-Dry Irrigation

Effects of Nitrogen-Loaded Biochar on Rice Growth, Nitrogen Uptake and Nitrogen Concentration Changes in Surface Water Under Alternate Wet-Dry Irrigation

Characteristics of root‐associated bacterial community and nitrogen biochemical properties of twoJaponicarice cultivars with different yields

AbstractRoot‐associated microbiomes play pivotal roles in rice plant nutrition and productivity. We studied how the Liaoxing 1 and Akitakomachi rice cultivars, which are characterized by high and low yields, respectively, modified the nutrient content, enzymatic activities in the rhizosphere, and bacterial community structure in the root endosphere, rhizosphere, and bulk soil with and without nitrogen application. Rice genotype and nitrogen application amount are both essential driving factors for changes in the nutrient content, enzymatic activities, and bacterial community. Bacterial community structure varied significantly across the three root‐associated compartments, and rhizosphere and bulk soil harbored significantly higher diversity and richness of bacteria than root endophytes. Bacterial communities in the root endosphere are mainly structured by rice cultivars. Nitrogen fertilization application influenced the compositions and functions of bacterial groups across the three compartments.Prolixibacteriaceae, as nitrogen‐fixing bacteria, were significantly enriched in the rhizosphere, and the relative abundance in the rhizosphere of the high‐yield cultivar was higher than that of the low‐yield cultivar. Rice genotype and nitrogen application amount are both essential driving factors for changes in nutrient content and enzymatic activities. In this study, it was found that the higher available nitrogen content and soil enzymatic activities in the rhizosphere of the high‐yield rice cultivar promoted rice nitrogen use, and they ultimately formed a positive feedback loop. Our results indicated that root‐associated bacterial communities combined with soil enzymatic activities strengthen the transformation of nitrogen nutrients, suggesting that the interactions could represent a mechanism for enhancing rice yield.

Engineered Urea-Doped Hydroxyapatite Nanomaterials as Nitrogen and Phosphorus Fertilizers for Rice

The application of nanomaterials as nanofertilizers is one of the advanced solutions to overcome the excessive use of conventional fertilizers without compromising the yield. In this study, the synthesized urea-doped hydroxyapatite nanomaterials (UHN) at recommended (UHN_RD) and half-recommended (UHN_HRD) doses were compared with a recommended dose of commercial bulk urea fertilizer (BUF) and control (CNT) treatment for nutrient availability in soil and yield of rice crops. Rice was grown in 12 field columns (four treatments × three replications) by applying the fertilizer treatments at four growth stages and irrigating the columns conventionally. The crop growth parameters such as plant height, biomass, and yield were measured for all columns. The depths of ponding water and drainage were measured daily, and the water samples collected from ponding water and drainage were analyzed for ammonium (NH4-N), nitrate (NO3-N), and ortho phosphorus (PO4-P) concentrations. The grain yield was increased by 61, 60, and 65% in BUF, UHN_HRD, and UHN_RD, respectively, compared to the CNT treatment, which indicates that the UHN can result in a yield at par with commercial fertilizers. The concentrations of NH4-N, NO3-N, and PO4-P in the leachate were reduced by 69.11, 16.3, and 87%, respectively, under UHN_HRD and by 60, 10.6, and 66.3%, respectively, under UHN_RD compared to BUF. The nutrient use efficiency was the highest in UHN_HRD for nitrogen (76.5%) and phosphorus (14.27%) nutrients. The application of UHN as nitrogen and phosphorus sources revealed yield improvement and reduced leaching of nutrients. Therefore, UHN could be used both as a nitrogen and phosphorus supplement to rice crops at a reduced application rate.

OsCBL1 affects rice seedling growth by modulating nitrate and phosphate responses.

To sustain high crop yield, a comprehensive understanding of the processes by which plants sense and acquire nutrients is of great importance. For the efficiency of crop fertilizer, it is essential to exploring the the signaling networks that coordinate the usage of nitrogen and phosphorus, the most demanding two mineral nutrients in plants. Here, we found that a protein OsCBL1 (Calcineurin B-like protein 1) is involved in the regulation of nitrogen and phosphorus signaling in rice. The nitrogen element, existing as ammonium or nitrate in the environment, affects nitrate signaling in vivo and root growth. Compared with the wild type, knockdown of OsCBL1 inhibit the growth of rice to the same extent, when nitrogen is deficient or nitrogen is present in the form of ammonium-nitrate mixture. The growth inhibition by OsCBL1-knockdown is more pronounced when nitrogen is present as ammonium. The phosphorus starvation-responsive genes is also regulated by the compound of nitrogen present in vitro and OsCBL1, while the phosphorus content is not affected. These results suggest that OsCBL1 may be involved in the response of rice to nitrogen and phosphorus nutrition in the environment, as well as the regulation of rice growth by environmental nutrition.

Estimation of nitrogen nutrition index in rice from UAV RGB images coupled with machine learning algorithms

Rapid and accurate estimation of rice Nitrogen Nutrition Index (NNI) is beneficial for management of nitrogen application in rice production. Traditional estimation methods required manual actual measurement data in the field, which was time-consuming and cost-expensive, and RGB images from unmanned aerial vehicle (UAV) provided an alternative option for nitrogen nutrition index (NNI) monitoring. In this study, RGB images from unmanned aerial vehicle (UAV) were obtained from each growth period of rice, and six machine learning (ML) algorithms, i.e., adaptive boosting (AB), artificial neural network (ANN), K-nearest neighbor (KNN), partial least squares (PLSR), random forest (RF) and support vector machine (SVM), were used to extract target information for estimating NNI as well as vegetation index (VI). Results showed that most UAV VIs were significantly correlated with rice NNI at the key growing periods; the estimation results of rice NNI using six ML algorithms showed that the RF algorithms performed the best at each growth period with the determination coefficient (R2) ranged from 0.88 to 0.96 and room mean square error (RMSE) ranged from 0.03 to 0.07, in which the estimation of NNI was the best in filling period and the early jointing stage. Rice NNI at the early jointing stage was significantly correlated with soil available nitrogen (AN) with the R2 of 0.84 in Pukou and 0.72 in Luhe, respectively, and rice NNI was significantly correlated with the yield with the R2 of more than 0.7 in Pukou at the whole period and more than 0.7 in Luhe from late jointing to maturity stage. Therefore, the combination of RGB images from UAV and ML algorithms was a scalable, simple and inexpensive method for rapid qualification of rice NNI, which effectively improved nitrogen use efficiency and provided guidance for precision fertilization in rice production.

Detection and Dynamic Variation Characteristics of Rice Nitrogen Status after Anthesis Based on the RGB Color Index

We aimed to elucidate the color changes of rice leaves after anthesis and create an algorithm for monitoring the nitrogen contents of rice leaves and of the whole plant. Hence, we aimed to provide a theoretical basis for the precise management of rice nitrogen fertilizer and the research and development of digital image nutrition monitoring equipment and reference. We selected the leaf colors of the main stems of four major rice varieties promoted in production, including Huaidao 5 (late-maturing medium japonica rice), Yangjing 4227 (early maturing late japonica rice), Changyou 5 (late japonica hybrid rice), and Yongyou 8 (late japonica hybrid rice). Under different nitrogen levels, the leaf R, G, and B values of the four rice varieties at different stages after anthesis, the dynamic changes in RGB normalized values, the correlations between RGB normalized values and leaf SPAD values, the leaf nitrogen content and whole plant nitrogen content, and the nitrogen prediction model were studied. The research results demonstrate the following: (1) regardless of nitrogen levels, the leaf of R, G, B, NRI, NGI and NBI of different rice varieties after anthesis followed the order, G &gt; R &gt; B. R, G, NRI, NGI, and days after heading could be fitted according to a logarithmic equation, y = aebx (0.726 ≤ R2 ≤ 0.992); B, NBI, and days after heading could be fitted using a linear equation, y = a + bx (0.863 ≤ R2 ≤ 0.992). Both fitting effects were significant (except NGI). (2) A quadratic function (Y = −1296.192x2 + 539.419x − 10.914; Y = −1173.104x2 + 527.073x − 12.993) was adopted to construct a monitoring model for the NBI and SPAD values of japonica rice and hybrid japonica rice leaves after anthesis and the R2 values were 0.902 and 0.838, respectively. Exponential functions (Y = 5.698e7.261x; Y = 3.371e9.326x) were employed to construct monitoring models of leaf nitrogen content, and the R2 values were 0.833 and 0.706, respectively. Exponential functions (Y = 5.145e4.9143x; Y = 3.966e5.364x) were also used to construct a monitoring model for the nitrogen content of the whole plant, and the R2 values were 0.737 and 0.511, respectively. The results obtained from prediction tests by using Determination Coefficient (R2), Relative Percent Deviation (RPD), and Root Mean Square Error (RMSE) showed that it was feasible, accurate, and efficient to use a scanner for measuring the nitrogen content of rice.

Effects of Dense Planting with Less Nitrogen Fertilization on Rice Yield and Nitrogen Use Efficiency in Northeast China

Effects of Dense Planting with Less Nitrogen Fertilization on Rice Yield and Nitrogen Use Efficiency in Northeast China

Biochemical mechanism of rice nitrogen promoting the resistance development of Nilaparvata lugens (Stål) to buprofezin

• Overusing nitrogen fertilizer impacts buprofezin’ efficacy to Nilaparvata lugens . • Rice nitrogen facilitates the resistance development of N. lugens to buprofezin. • Increased esterase activity may be the resistance mechanism in N. lugens . • The conclusion will improve the integrated pest and nutrient management strategies. Overusing nitrogen fertilizer not only pollute farmlands, but also make Nilaparvata lugens (Stål) less susceptible to pesticides. The current study investigated the relationship between nitrogen fertilizer application and buprofenzin resistance in N. lugens in rice by conducting a series of field efficacy tests and laboratory bioassays. The results showed that the efficacy of buprofezin decreased significantly with high level of nitrogen fertilizer application, compared to those with low or no nitrogen application in rice fields. In the laboratory, the resistance ratios of N. lugens to buprofezin, assayed at three concentrations of nitrogen (0, 1.0, 3.0 mmol/L), have developed to 14.05-, 18.40- and 25.81-fold after 20 generations of resistance selection, respectively. Meanwhile, the resistance ratios of N. lugens without buprofezin treated were 1.00-, 3.30- and 4.67-fold after 20 generations as the nitrogen concentrations increased. The enzymatic assays revealed that the activities of P450 and esterase increased significantly after resistance selection with buprofezin and nitrogen, especially on the esterase activity in N. lugens under the condition of nitrogen treatment. These results suggested that nitrogen fertilizer application contributed to the resistance development in N. lugens to buprofezin by enhancing the activity of esterase.

Estimation of Paddy Rice Nitrogen Content and Accumulation Both at Leaf and Plant Levels from UAV Hyperspectral Imagery

Remote sensing-based mapping of crop nitrogen (N) status is beneficial for precision N management over large geographic regions. Both leaf/canopy level nitrogen content and accumulation are valuable for crop nutrient diagnosis. However, previous studies mainly focused on leaf nitrogen content (LNC) estimation. The effects of growth stages on the modeling accuracy have not been widely discussed. This study aimed to estimate different paddy rice N traits—LNC, plant nitrogen content (PNC), leaf nitrogen accumulation (LNA) and plant nitrogen accumulation (PNA)—from unmanned aerial vehicle (UAV)-based hyperspectral images. Additionally, the effects of the growth stage were evaluated. Univariate regression models on vegetation indices (VIs), the traditional multivariate calibration method, partial least squares regression (PLSR) and modern machine learning (ML) methods, including artificial neural network (ANN), random forest (RF), and support vector machine (SVM), were evaluated both over the whole growing season and in each single growth stage (including the tillering, jointing, booting and heading growth stages). The results indicate that the correlation between the four nitrogen traits and the other three biochemical traits—leaf chlorophyll content, canopy chlorophyll content and aboveground biomass—are affected by the growth stage. Within a single growth stage, the performance of selected VIs is relatively constant. For the full-growth-stage models, the performance of the VI-based models is more diverse. For the full-growth-stage models, the transformed chlorophyll absorption in the reflectance index/optimized soil-adjusted vegetation index (TCARI/OSAVI) performs best for LNC, PNC and PNA estimation, while the three band vegetation index (TBVITian) performs best for LNA estimation. There are no obvious patterns regarding which method performs the best of the PLSR, ANN, RF and SVM in either the growth-stage-specific or full-growth-stage models. For the growth-stage-specific models, a lower mean relative error (MRE) and higher R2 can be acquired at the tillering and jointing growth stages. The PLSR and ML methods yield obviously better estimation accuracy for the full-growth-stage models than the VI-based models. For the growth-stage-specific models, the performance of VI-based models seems optimal and cannot be obviously surpassed. These results suggest that building linear regression models on VIs for paddy rice nitrogen traits estimation is still a reasonable choice when only a single growth stage is involved. However, when multiple growth stages are involved or missing the phenology information, using PLSR or ML methods is a better option.

Rapid Identification of Rice Macronutrient Content in Saline Soils Using Smartphone Camera

Abstract Indonesia’s rice production has decreased by 6.83% (on average) in the last five years (2015 – 2019) because of some factors. Salinity (42%) is one of the leading factors that cause decreasing rice production besides climate change (21%), drought (9%), and other factors (28%). The smartphone camera serves as an alternative technology to prevent macronutrient deficiencies due to salinity. This study used aerial photos from android with visible light (R, G, and B), and the image was taken from a height of 5 m. The observation of macronutrient content in plant biomass was carried out using a free grid to adjust rice fields and saline soil. The formula was obtained from regression analysis and paired t-test between the biomass macronutrient and the extracted digital number of aerial photographs that have been stacked. The results showed that digital number (DN) from a smartphone was reliable to predict nitrogen (N), phosphorus (P), and potassium (K) content in rice with formula N = 0.0035 * DN + 0.8192 (R 2 0.84), P = 0.0049 * DN – 0.2042 (R 2 0.70), and K = 0.0478 * DN – 2.6717 (R 2 0.70). There was no difference between the macronutrient estimation results from the formula and the field’s original data.

Sulfoquinovosyl diacylglycerol synthase 1 impairs glycolipid accumulation and photosynthesis in phosphate-deprived rice

Phosphate (Pi)-starved crops utilize phospholipids as a source for internal Pi supply by replacing non-phosphorus glycolipids. In rice, sulfoquinovosyl diacylglycerol synthase 1 (OsSQD1) functions as a key enzyme in the first step to catalyze sulfoquinovosyldiacylglycerol (SQDG) formation. Here we study differential expression of OsSQD1 in response to Pi, nitrogen, potassium, and iron-deficiencies in rice. Electrophoretic mobility shift assay suggested that OsSQD1 is regulated by OsPHR2 (Phosphate Starvation Response2), a MYB (v-myb avian myeloblastosis viral oncogene homolog) domain-containing transcription factor. The concentrations of different lipid species in ossqd1 knockout mutant demonstrated that OsSQD1 silencing increased the phospholipid content and altered fatty acid composition under Pi-deficiency. Moreover, OsSQD1 silencing reduces glycolipid accumulation under Pi-deficiency, and triggered the saturation of fatty acids in phospholipids and glycolipids treated with different Pi regimes. Relative amounts of transcripts related to phospholipid degradation and glycolipid synthesis were assessed to explore the mechanism by which OsSQD1 exerts an effect on lipid homeostasis under P-deficiency. Furthermore, OsSQD1 silencing inhibited photosynthesis, especially under Pi-deficient conditions, by down-regulating glycolipids in rice shoots. Taken together, our study reveals that OsSQD1 plays a key role in lipid homeostasis, especially glycolipid accumulation under Pi-deficiency, which results in the inhibition of photosynthesis.

Effects of rice straw biochar and nitrogen fertilizer on ramie (Boehmeria nivea L.) morpho-physiological traits, copper uptake and post-harvest soil characteristics, grown in an aged-copper contaminated soil

Copper (Cu) contamination in soils is becoming a serious problem. Therefore, an experiment in plastic pots was carried out to investigate interactive influence of rice straw BC (BC0:0, BC1:5, and BC2:10% w/w) and nitrogen fertilizer (N0:0, N1:140, N2:280, and N3:420 kg ha − 1) on plant growth, Cu mobility and phytoavailability to Boehmeria nivea in Cu polluted soil. Results revealed that BC × N fertilizer had significantly (p ≤ 0.05) increased the growth of B. nivea in terms of biomass, height of plant, diameter of stem and number of leaves. Furthermore, BC × N fertilizer resulted in significant changes in pH, electrical conductivity and cation exchange capacity of soil after harvesting in comparison with control. However, the influence of BC × N fertilizer on soil extractable Cu and Cu uptake by plant varied with levels of N fertilizer. The BC2N1 treatment significantly increased the shoot biomass of B. nivea by 635% (fresh biomass) and 452% (dry biomass), but reduced Cu contents in roots, stems and leaves i.e., 52, 23 and 34 mg kg − 1, respectively. Thereby, high dose of BC along with low N fertilizer could be considered as an efficient soil amendment combination for Cu stabilization and higher biomass production of B. nivea in highly Cu contaminated soil.

Knockdown of OsSAE1a affects acquisition and mobilization of nitrogen, and growth and development of rice

Knockdown of OsSAE1a affects acquisition and mobilization of nitrogen, and growth and development of rice

Effect of Sources, Split and Foliar Application of KCl and KClO3 on Availability and Uptake of Nitrogen in Aerobic Rice

Aim: To investigate the effect of KCl and KClO3 as sources of potassium in aerobic rice with four types of split doses and two levels of foliar applications of potassium.&#x0D; Study Design: The experiment was laid out in Randomized Block Design with three replications.&#x0D; Place and Duration of Study: Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal, Puducherry.&#x0D; Methodology: The rice variety PMK 4 was tested with two sources of potassium viz., Potassium chloride (KCl) and Potassium chlorate (KClO3), four types of split application viz., K control (S1), basal with no split (S2), two splits (S3) and three splits (S4) along with foliar application treatments viz., no foliar (F1) and foliar spray (F2).&#x0D; Results: The results of field experiment revealed that the N availability in soil was more at all stages of crop growth by two and three split doses of potassium. The KClO3 increased the available N status at active and panicle initiation stages. Whereas in flowering stage, the KCl recorded the higher available N status in soil. The nitrogen uptake at active tillering stage and flowering stage was evidently improved with three split doses of potassium. Whereas in panicle initiation stage, the two split doses registered higher N uptake. The nitrogen uptake by both grain and straw was conspicuously higher in three and two split doses of potassium.&#x0D; Conclusion: The split applications tested in this investigation influenced the available N status in soil. Almost in all the stages, three split applications retained more available N in soil. This implies the positive interaction of potassium with nitrogen.

Recent Advances on Nitrogen Use Efficiency in Rice

Rice (Oryza sativa L.) is a daily staple food crop for more than half of the global population and improving productivity is an important task to meet future demands of the expanding world population. The application of nitrogen (N) fertilization improved rice growth and productivity in the world, but excess use causes environmental and economic issues. One of the main goals of rice breeding is reducing N fertilization while maintaining productivity. Therefore, enhancing rice nitrogen use efficiency (NUE) is essential for the development of sustainable agriculture and has become urgently needed. Many studies have been conducted on the main steps in the use of N including uptake and transport, reduction and assimilation, and translocation and remobilization, and on transcription factors regulating N metabolism. Understanding of these complex processes provides a base for the development of novel strategies to improve NUE for rice productivity under varying N conditions.

Research advance in the roles of water-nitrogen-oxygen factors in mediating rice growth, photosynthesis and nitrogen utilization in paddy soils.

Water and nitrogen are two important factors controlling rice growth and development. Suitable water-nitrogen interaction can alter nitrogen forms and oxygen environmental factors via regulating water content in the rhizosphere of paddy soil, promote the construction of root morphology, improve leaf photosynthesis and the allocation equilibrium of the photosynthetic products between the source and sink organs, and consequently increase rice population quality and grain yield. The microbial regulation mechanisms driven by the environmental factors (e.g. water, nitrogen and oxygen) also play an important role in improving nitrogen utilization efficiency in rice-soil system. Here, we reviewed the research progress in water-nitrogen interaction, and briefly discussed the effects of water, nitrogen form, and dissolved oxygen on rice growth, photosynthesis, carbon and nitrogen metabolism, nitrogen conversion and the underlying microbiological mechanism. We proposed several key directions for future researches: 1) to quantitatively investigate the spatial and temporal variations of dissolved oxygen in rhizosphere and their dominant environmental drivers under different water and nitrogen regimes; 2) to evaluate the responses of root-sourced signal to rhizosphere dissolved oxygen in different rice genotypes, and uncover its intrinsic mechanisms involved in rice growth and development; 3) to investigate the effects of key microbial process driven by the rhizosphere oxygen environment on the soil nitrogen conversion and rice nitrogen utilization.

Effects of topsoil removal on nitrogen uptake, biomass accumulation, and yield formation in puddled-transplanted rice

• Topsoil removal reduced total N uptake, total dry biomass, and grain yield of rice. • Topsoil had the largest contribution to plant N uptake from midtillering to panicle initiation. • Topsoil removal had the largest effect on panicles m −2 among yield components. • Total dry biomass rather than harvest index was affected by topsoil removal. Rice nitrogen (N) uptake and yield formation depend on both applied N fertilizer and soil-derived N. In this study, we determined the effects of topsoil removal on the N uptake and yield formation of rice crop. Four rice varieties were grown in farmers’ fields in Wuxue County, Hubei Province, China in 2016–2018 under the treatments of topsoil removal (TR) and control (CK). The TR treatment was established by desurfacing soil at about half of the topsoil depth (11−15 cm). Experiments were conducted in three adjacent fields in the three years and 100 kg N ha −1 was applied in all plots except for zero-N treatment in 2018. Averaged across years, N treatments, and varieties, topsoil removal reduced total N uptake by 27.8 %. The period from midtillering to panicle initiation had the highest daily N uptake from topsoil compared with other growing periods. During this growing period, the percentage of N uptake from topsoil to plant N uptake ranged from 54.2 to 62.4 % with an average value of 56.4 % across both zero-N and N-applied treatments. On average, topsoil removal reduced grain yield by 16.7 % and total dry biomass by 17.6 %. Among yield components, panicles m −2 was mainly responsible for the yield reduction in TR. Furthermore, total dry biomass rather than harvest index explained the yield reduction in TR compared with CK. Our results suggest that topsoil provided substantial N to rice crop especially during the period from midtillering to panicle initiation for achieving higher grain yield through increased panicles m −2 and biomass production.