Optimizing phosphate fertilizer input to reduce phosphorus loss in rice-oilseed rape rotation.

Identifying the major sources and critical periods of P loss from agricultural fields provides important guidance for reducing P loss. A rice-oilseed rape rotation with no P fertilization (NP, control), medium P fertilization (MP, 90 kg P2O5 ha-1 season-1), and high P fertilization (HP, 180 kg P2O5 ha-1 season-1) was conducted from 2019 to 2021 in the middle Yangtze River Basin. Runoff and leaching P losses were measured simultaneously using runoff event monitoring and a percolation device. Applying P fertilizer increased the P concentration in the field ponding water and percolation water of the rice-oilseed rape rotation. During the rice growing season, total P (TP), dissolved P (DP), and particulate P (PP) concentrations in the field ponding water and percolation water peaked 1 day after P was applied, and then decreased rapidly. After 10 days of fertilization, P concentration in the field ponding water of the MP treatment decreased to a minimum and stabilized, while the HP treatment extended this period to 20 days. The highest P concentration in percolation water was observed at the first sampling during the oilseed rape season, and then it continued to decrease. Inputting P fertilizer increased P loss by 55.0-109.9% compared to the NP treatment, with annual P losses of 0.89-1.10 kg P ha-1, of which runoff loss accounted for 61.7-62.9%. Fertilization and precipitation resulted in varied P loss within and between seasons. Runoff from heavy precipitation during the rice season was the main source of P loss, while PP accounted for 54.7-77.6% of runoff P loss. The strong utilization of soil P by rice resulted in a lower demand for exogenous P fertilizer than oilseed rape. Excessive P input increased the soil P surplus and vertical migration. Therefore, reducing rice season P fertilizer inputs to achieve annual P balance in rice-oilseed rape rotation can effectively reduce soil P surplus and loss while ensuring crop P demand, and the initial 10 d after fertilization in the rice season was a critical period for reducing P runoff loss.

Sufficient potassium improves inorganic phosphate-limited photosynthesis in Brassica napus by enhancing metabolic phosphorus fractions and Rubisco activity.

Crop photosynthesis (A) and productivity are often limited by a combination of nutrient stresses, such that changes in the availability of one nutrient may affect the availability of another nutrient, in turn influencing A. In this study, we examined the synergistic effects of phosphorus (P) and potassium (K) on leaf A in a nutrient amendment experiment, in which P and K were added individually or in combination to Brassica napus grown under P and K co-limitation. The data revealed that the addition of P gradually removed the dominant limiting factor (i.e. the limited availability of P) and improved leaf A. Strikingly, the addition of K synergistically improved the overall uptake of P, mainly by boosting plant growth, and compensated for the physiological demand for P by prioritizing investment in metabolic pools of P (P-containing metabolites and inorganic phosphate, Pi). The enlarged pool of metabolically active P was partially associated with the upregulation of Pi regeneration through release from triose phosphates rather than replacement of P-containing lipids. This process mitigated P restrictions on A by maintaining the ATP/NADPH and NADPH/NADP+ ratios and increasing the content and activity of Rubisco. Our findings demonstrate that sufficient K increased Pi-limited A by enhancing metabolic P fractions and Rubisco activity. Thus, ionic synergism may be exploited to mitigate nutrient-limiting factors to improve crop productivity.

Nutrition-mediated cell and tissue-level anatomy triggers the covariation of leaf photosynthesis and leaf mass per area.

Plants in nutrient-poor habitats converge towards lower rates of leaf net CO2 assimilation (Aarea); however, they display variability in leaf mass investment per area (LMA). How a plant optimizes its leaf internal carbon investment may have knock-on effects on structural traits and, in turn, affect leaf carbon fixation. Quantitative models were applied to evaluate the structural causes of variations in LMA and their relevance to Aarea in rapeseed (Brassica napus) based on their responses to nitrogen (N), phosphorus (P), potassium (K), and boron (B) deficiencies. Leaf carbon fixation decreased in response to nutrient deficiency, but the photosynthetic limitations varied greatly depending on the deficient nutrient. In comparison with Aarea, the LMA exhibited diverse responses, being increased under P or B deficiency, decreased under K deficiency, and unaffected under N deficiency. These variations were due to changes in cell- and tissue-level carbon investments between cell dry mass density (N or K deficiency) and cellular anatomy, including cell dimension and number (P deficiency), or both (B deficiency). However, there was a conserved pattern independent of nutrient-specific limitations-low nutrient availability reduced leaf carbon fixation but increased carbon investment in non-photosynthetic structures, resulting in larger but fewer mesophyll cells with a thicker cell wall but a lower chloroplast surface area appressed to the intercellular airspace, which reduced the mesophyll conductance and feedback-limited Aarea. Our results provide insight into the importance of mineral nutrients in balancing the leaf carbon economy by coordinating leaf carbon assimilation and internal distribution.

Diagnosis of Nitrogen Nutrition in Rice Leaves Influenced by Potassium Levels.

Evaluation of nitrogen (N) status by leaf color is a kind of classic nutritional diagnostic method. However, the color of leaves is influenced not only by N, but also by other nutrients such as potassium (K). Two-year field trials with a factorial combination of N and K were conducted to investigate the effects of different N and K rates on soil plant analysis development (SPAD) readings and leaf N, K, magnesium (Mg), and chlorophyll concentrations. Visual inspections in leaf greenness revealed darker green leaves with increasing N rates, while paler green leaves with increasing K rates. Data showed that SPAD readings, chlorophyll, N and Mg concentrations, and the chloroplast area increased significantly with raising N rates, while declined sharply with the increase in K rates due to the antagonistic relationships between K+ and NH4 + as well as Mg2+. It was also probable that the increase in K promoted the growth of leaves and diluted their N and Mg concentrations. The paler leaf appearance resulting from the application of K may overestimate the actual demand for N in the diagnosis of rice N status. The strong antagonistic relationships between K+, NH4 +, and Mg2+ should be considered in rice production and fertilization.

Interactive effects of nitrogen and potassium on photosynthesis and photosynthetic nitrogen allocation of rice leaves.

BACKGROUND: Nitrogen (N) and potassium (K) are two important mineral nutrients in regulating leaf photosynthesis. Studying the interactive effects of N and K on regulating N allocation and photosynthesis (Pn) of rice leaves will be of great significance for further increasing leaf Pn, photosynthetic N use efficiency (PNUE) and grain yield. We measured the gas exchange of rice leaves in a field experiment and tested different kinds of leaf N based on N morphology and function, and calculated the interactive effects of N and K on N allocation and the PNUE. RESULTS: Compared with N0 (0 kg N ha- 1) and K0 (0 kg K2O ha- 1) treatments, the Pn was increased by 17.1 and 12.2% with the supply of N and K. Compared with N0K0 (0 kg N and 0 kg K2O ha- 1), N0K120 (0 kg N and 120 kg K2O ha- 1) and N0K180 (0 kg N and 180 kg K2O ha- 1), N supply increased the absolute content of photosynthetic N (Npsn) by 15.1, 15.5 and 10.5% on average, and the storage N (Nstore) was increased by 32.7, 64.9 and 72.7% on average. The relative content of Npsn was decreased by 5.6, 12.1 and 14.5%, while that of Nstore was increased by 8.7, 27.8 and 33.8%. Supply of K promoted the transformation of Nstore to Npsn despite the leaf N content (Na) was indeed decreased. Compared with N0K0, N180K0 (180 kg N and 0 kg K2O ha- 1) and N270K0 (270 kg N and 0 kg K2O ha- 1), K supply increased the relative content of Npsn by 17.7, 8.8 and 7.3%, and decreased the relative content of Nstore by 24.2, 11.4 and 8.7% respectively. CONCLUSIONS: This study indicated the mechanism that K supply decreased the Na but increased the Npsn content and then increased leaf Pn and PNUE from a new viewpoint of leaf N allocation. The supply of K promoted the transformation of Nstore to Npsn and increased the PNUE. The decreased Nstore mainly resulted from the decrease of non-protein N. Combined use of N and K could optimize leaf N allocation and maintain a high leaf Npsn content and PNUE.

Synergistic Effects of Nitrogen and Potassium on Quantitative Limitations to Photosynthesis in Rice ( Oryza sativa L.).

The inhibition of the net CO2 assimilation ( A) during photosynthesis is one of the major physiological effects of both nitrogen (N) and potassium (K) deficiencies on rice growth. Whether the reduction in A arises from a limitation in either the diffusion and biochemical fixation of CO2 or photochemical energy conversion is still debated in relation to N and K deficiencies. In this study, the gas exchange parameters of rice under different N and K levels were evaluated and limitations within the photosynthetic carbon capture process were quantified. A was increased by 17.3 and 12.1% for the supply of N and K, respectively. The suitable N/K ratio should be maintained from 1.42 to 1.50. The limitation results indicated that A is primarily limited by the biochemical process. The stomatal conductance ( LS), mesophyll conductance ( LM), and biochemical ( LB) limitations were regulated by 26.6-79.9, 24.4-54.1, and 44.1-75.2%, respectively, with the N and K supply.

Biologically-motivated system identification: application to microbial growth modeling.

This paper presents a new method for identification of system models that are linear in parametric structure, but arbitrarily nonlinear in signal operations. The strategy blends traditional system identification methods with three modeling strategies that are not commonly employed in signal processing: linear-time-invariant-in-parameters models, set-based parameter identification, and evolutionary selection of the model structure. This paper reports recent advances in the theoretical foundation of the methods, then focuses on the operation and performance of the approach, particularly the evolutionary model determination. The method is applied to the modeling of microbial growth by Monod Kinetics.