Phosphorus availability and dynamics in soil affected by long-term ruzigrass cover crop

Responses of soil enzymatic activities and microbial biomass phosphorus to improve nutrient accumulation abilities in leguminous species

Fertilizers application are widely used to get a higher yield in agricultural fields. Nutrient management can be improved by cultivating leguminous species in order to obtain a better understanding of the mechanisms that increase the amount of available phosphorus (P) and potassium (K) through fertilizer treatments. A pot experiment was conducted to identify the leguminous species (i.e., chickpea and pea) under various fertilizer treatments. Experimental design is as follows: T0 (control: no fertilizer was applied), T1: P applied at the level of (90 kg ha-1), T2: (K applied at the level of 90 kg ha-1), and T3: (PK applied both at 90 kg ha-1). All fertilizer treatments significantly (p < 0.05) improved the nutrient accumulation abilities and enzymes activities. The T3 treatment showed highest N uptake in chickpea was 37.0%, compared to T0. While T3 developed greater N uptake in pea by 151.4% than the control. However, T3 treatment also increased microbial biomass phosphorus in both species i.e., 95.7% and 81.5% in chickpeas and peas, respectively, compared to T0 treatment. In chickpeas, T1 treatment stimulated NAGase activities by 52.4%, and T2 developed URase activities by 50.1% higher than control. In contrast, T3 treatment enhanced both BGase and Phase enzyme activities, i.e., 55.8% and 33.9%, respectively, compared to the T0 treatment. Only the T3 treatment improved the activities of enzymes in the pea species (i.e., BGase was 149.7%, URase was 111.9%, Phase was 81.1%, and NAGase was 70.0%) compared to the control. Therefore, adding combined P and K fertilizer applications to the soil can increase the activity of enzymes in both legume species, and changes in microbial biomass P and soil nutrient availability make it easier for plants to uptake the nutrients.

Enhancing estimation of cover crop biomass using field-based high-throughput phenotyping and machine learning models

Incorporating cover crops into cropping systems offers numerous potential benefits, including the reduction of soil erosion, suppression of weeds, decreased nitrogen requirements for subsequent crops, and increased carbon sequestration. The aboveground biomass (AGB) of cover crops strongly influences their performance in delivering these benefits. Despite the significance of AGB, a comprehensive field-based high-throughput phenotyping study to quantify AGB of multiple cover crops in the U.S. Midwest has not been found. This study presents a two-year field experiment carried out in Eastern Nebraska, USA, to estimate AGB of five different cover crop species [canola (Brassica napus L.), rye (Secale cereale L.), triticale (Triticale × Triticosecale L.), vetch (Vicia sativa L.), and wheat (Triticum aestivum L.)] using high-throughput phenotyping and Machine Learning (ML) models. Destructive AGB sampling was performed three times during each spring season in 2022 and 2023. An array of morphological, spectral, thermal, and environmental features from the sensors were utilized as feature inputs of ML models. Moderately strong linear correlations between AGB and the selected features were observed. Four ML models, namely Random Forests Regression (RFR), Support Vector Regression (SVR), Partial Least Squares Regression (PLSR), and Artificial Neural Network (ANN), were investigated. Among the four models, PLSR achieved the highest Coefficient of Determination (R2) of 0.84 and the lowest Root Mean Squared Error (RMSE) of 892 kg/ha (Normalized RMSE (NRMSE) = 8.87%), indicating that PLSR could be the most appropriate method for estimating AGB of multiple cover crop species. Feature importance analysis ranked spectral features like Normalized Difference Red Edge (NDRE), Solar-induced Fluorescence (SIF), Spectral Reflectance at 485 nm (R485), and Normalized Difference Vegetation Index (NDVI) as top model features using PLSR. When utilizing fewer feature inputs, ANN exhibited better prediction performance compared to other models. Using morphological and spectral parameters as input features alone led to a R2 of 0.80 and 0.77 for AGB prediction using ANN, respectively. This study demonstrated the feasibility of high-throughput phenotyping and ML techniques for accurately estimating AGB of multiple cover crop species. Further enhancement of model performance could be achieved through additional destructive sampling conducted across multiple locations and years.

Assessing the phosphorus cycle in European agricultural soils: Looking beyond current national phosphorus budgets

Phosphorus (P) is an essential nutrient for all crops, yet its excess negatively affects public health, the environment, and the economy. At the same time, rock P is a critical raw material due to its importance for food production, the finite geological deposits, and its unequal regional distribution. As a consequence, nutrient management is addressed by numerous environmental policies. Process-based biogeochemical models are valuable instruments to monitor the P cycle and predict the effect of agricultural management policies. In this study, we upscale the calibrated DayCent model at European level using data-derived soil properties, advanced input data sets, and representative management practices. Our results depicted a P budget with an average P surplus (0.11 kg P ha-1 year-1), a total soil P (2240.0 kg P ha-1), and available P content (77.4 kg P ha-1) consistent with literature and national statistics. Through agricultural management scenarios, we revealed a range of potential changes in the P budget by 2030 and 2050, influenced by the interlink of P with biogeochemical carbon and nitrogen cycles. Thus, we developed a powerful assessment tool capable of i) identifying areas with P surplus or deficit at high spatial resolution of 1 km2, (ii) pinpointing areas where a change in agricultural management would be most urgent to reach policy goals in terms of environmental pollution, food security and resource efficiency of a critical raw material, and iii) assessing the response of the P cycle to modifications in agricultural management.

Evaluation of the distribution and mobility of labile phosphorus in sediment profiles of Lake Nansi, the largest eutrophic freshwater lake in northern China

Understanding various biogeochemical processes, especially in eutrophic sediments, necessitates fine-scale phosphorus (P) measurements in pore waters. To the best of our knowledge, the fine-scale distributions of P across the sediment profiles of Lake Nansi have rarely been investigated. Herein we evaluated the dynamic distributions of labile P and Fe across the sediment-water interface (SWI) of Lake Nansi at two-dimensional (2D) and sub-millimeter resolution, using well-established colorimetric diffusive gradients in thin films (DGT) methodology. The concentrations of labile P in all investigated sediment profiles exhibited strong spatial variations, ranging from 0 to 1.50 mg/L with a considerable number of hotspots. Lake Nanyang (0.55 ± 0.21 mg/L) had the highest mean concentration of labile P, followed by Lake Dushan (0.38 ± 0.19 mg/L), Lake Weishan (0.28 ± 0.21 mg/L), and Lake Zhaoyang (0.18 ± 0.09 mg/L). The highest concentrations of labile P were always detected in Lake Dushan, which had been subjected to excessive exogenous P pollution. The co-distributions of labile P and Fe in the majority of the sediment of Lake Nansi confirmed highly positive correlations (P < 0.01), suggesting that the mobility of labile P throughout the SWI was likely governed by iron redox processes. The apparent diffusion fluxes of P across the SWI ranged from -7.7 to 33.6 μg/m²·d, with a mean value of 5.26 ± 7.80 μg/m²·d. Positive apparent fluxes for labile P were recorded in most sediment cores, demonstrating the strong upward mobility of P from the sediment to the overlying water. Our results provided accurate and extensive information regarding the micro-distribution and dynamic exchange of labile P across the SWI. This allows for a better understanding of eutrophication processes and the implementation of P management strategies in Lake Nansi.

Characterization of internal phosphorus loading in the sediment of a large eutrophic lake (Lake Taihu, China)

Lake Taihu suffers from severe algal blooms every year, which is attributed primarily to the release of sediment phosphorus (P), namely the internal P loading. However, the overall internal P loading and the P hotspots in sediment have not been fully studied. This paper presents several methods, including sequential P extraction, the use of diffusive gradient in thin film (DGT), and intact core incubation to give a detailed investigation of sediment internal P loading as well as its roles in algal dominated zones (ADZs) and grass dominated zones (GDZs) in Lake Taihu. Sediment microbial composition was also analyzed to investigate its relationship with P fractions. The results indicate that the total P and the mobile P fraction in the ADZ sediments are generally higher than those of the GDZ sediments. The percentage of sediment mobile P to TP is similar to the mobile P in their distributions. In contrast, calcium bound P accounts for most of the TP in GDZ, while mobile P contributes the most to TP in ADZ. Overall, sediment can release 256 tons of TP and 217 tons of soluble reactive phosphorus (SRP) over a period of six months in the warmer seasons. Similarly, a high concentration of DGT-measured P was observed in ADZs that are recognized as P hotspots in Lake Taihu. Sediments in ADZ and GDZ was dominated by the bacteria Firmicutes and Proteobacteria, respectively and which were closely related with mobile P and calcium bound P in sediment, respectively. GZD seems to be able to retain more P in sediments, thereby reducing its contribution to of internal P loading. These results indicate that the difference in sediment composition between ADZ and GDZ affects their roles in sediment internal P loading, therefore, different management strategies should be used to combat sediment internal P loads in the two zones.

The spatio-temporal change in soil P and P-solubilizing bacteria under clover mulching in apple orchards of Loess Plateau

Cover crop is an effective practice for improving soil quality and increase soil nutrients. However, the spatio-temporal change of soil phosphorus (P) components and P-solubilizing microorganisms in the process of grass succession is not evident. Here, we studied the variation of soil P components and P-solubilizing bacteria at 0-60 cm soil layer under clean tillage (CT) and white clover (WC, Trifolium repens L.) grown for 5, 9, and 14 years in an apple test station on the Loess Plateau, China. This study suggested that clover cover could effectively increase the total P, available P (AP), microbial P, organic P (Po), and inorganic P (Al-P, Ca₂-P, Ca₈-P and Fe-P) in topsoil (0-20 cm) and AP, Po and inorganic P at 20-40 cm soil layer to improve the soil P bioavailability. The effects of WC living mulch on the soil P forms were more significant with the increase in grass growing years, but this effect was difficult to extend to deep soil. In addition, the WC treatments were beneficial to the growth of P-solubilizing microorganisms in surface soil and improved the alkaline phosphatase activity at 0-40 cm soil layer, mainly including Bacillus, Bradyrhizobium, Nocardioides, Sphingomonas and Streptomyces. This study provided a perspective on the dynamic changes of soil P forms and P-solubilizing microorganisms and under long-term cover crop.

Release characteristics and mechanisms of sediment phosphorus in contaminated and uncontaminated rivers: A case study in South China

Phosphorus (P) cycling present in sediments associated with iron (Fe), manganese (Mn) and sulfur (S) geochemical processes may cause secondary pollution in overlying water. Understanding the mechanisms of P release from sediments should help to restore water quality. This study used the diffusive gradients in thin film (DGT) technique to investigate the seasonal variation in the lability, remobilization mechanisms, and release characteristics of sediment P in the uncontaminated Xizhi River and the severely contaminated Danshui River, South China. P accumulation in sediments contributed to higher DGT-labile P concentrations in contaminated reaches, and the highest labile P concentrations were generally observed in summer season at each site. The significant positive relationships (p < 0.05) between labile Fe and P confirmed the Fe-P coupling release mechanism in uncontaminated sediments. Stronger relationships between labile Mn and P at contaminated sites indicated that Mn oxides played an important role in P remobilization. However, sulfate reduction associated with microbial activities (crucial genera: Desulfobulbus, Desulfomicrobium and Desulforhabdus) was considered to decouple the Fe & Mn-P cycling relationship, promoting P release at contaminated sites. The effluxes of sediment P were much higher in the Danshui River (mean 0.132 mg cm^-2·d^-1) than in the Xizhi River (mean 0.038 mg cm^-2·d^-1). And hot season led to growth in P effluxes that was much greater in contaminated river.

Effects of cropping system and fertilization regime on soil phosphorous are mediated by rhizosphere-microbial processes in a semi-arid agroecosystem

In semi-arid regions, soil phosphorus (P) dynamics in cereal-legume intercropping are not yet fully elucidated, particularly in relation to integrated application of fertilizers. To this aim, we investigate the effects of different fertilizers on various P fractions in relation to the rhizosphere-microbial processes in a cowpea/maize intercropping system. Field experiments were conducted during two consecutive years (2016-2017) in a split-plot design by establishing cowpea/maize alone or intercropped onto the main plot, while the sub-plot was treated with four types of fertilization, i.e. no fertilizer addition (control), organic amendment (compost), mineral fertilizers (NPK) and multi-nutrient enriched compost (NPKEC). Our results showed that NPKEC fertilizer increased NaHCO₃-P_i by 69% in maize, 62% in cowpea and 93% in intercropped plots compared to control plots. Similarly, a significant increase in the NaHCO₃-P_o fraction was also recorded with NPKEC treatment in all cropping systems. In case of moderately labile P, NPKEC fertilizer caused the highest increase of NaOH-P_o (12.87 ± 0.50 mg P kg^-1 soil) and NaOH-P_i (22.29 ± 0.83 mg P kg^-1 soil) fractions in intercropped plots. Except for intercropping, NPK application caused an increase in the non-available P fraction (HCl-P_i), while the use of NPKEC decreased the HCl-P_i concentration in all cropping systems, suggesting stronger merits both for intercropping and NPKEC. Surprisingly, maize exhibited substantially higher phosphatases activity compared to cowpea in monoculture amended with compost, implying distinct crop strategies for adaptation under low P conditions. Based on the multi-factor analysis, the close association of NaHCO₃-P with P solubilizing bacteria, root carboxylates and pH indicated that rhizosphere processes are the strongest predictors of immediately available P. Since alkaline phosphatase (ALP) is a P-degrading enzyme of microbial origin, rhizosphere related ALP association may have originated from root-associated microflora promoting P mobilization. Furthermore, the strong association of microbial biomass P (MBP) and acid phosphates (ACP) with NaOH-P fraction indicated moderately available P cycle in soil was mainly driven by microbial-related processes. Factor analysis map and two-way ANOVA confirmed that fertilization regime had a stronger effect on all tested variables compared to cropping system. Altogether, our results suggest that a combination of microbial-rhizosphere processes controls the dynamics of P fertility in semi-arid soils. In the broader context of improving soil P fertility, it is highly recommended the use of environmentally sustainable sources of fertilizer, such as NPKEC, which can enhance the competitive performance of legume-cereal intercropping under semi-arid agroecosystems.

EffHunter: A Tool for Prediction of Effector Protein Candidates in Fungal Proteomic Databases

Pathogens are able to deliver small-secreted, cysteine-rich proteins into plant cells to enable infection. The computational prediction of effector proteins remains one of the most challenging areas in the study of plant fungi interactions. At present, there are several bioinformatic programs that can help in the identification of these proteins; however, in most cases, these programs are managed independently. Here, we present EffHunter, an easy and fast bioinformatics tool for the identification of effectors. This predictor was used to identify putative effectors in 88 proteomes using characteristics such as size, cysteine residue content, secretion signal and transmembrane domains.