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Background and Aims The forage grass Brachiaria humidicola (Bh) has been shown to reduce soil microbial nitrification. However, it is not known if biological nitrification inhibition (BNI) also has an effect on nitrogen (N) cycling during cultivation of subsequent crops. Therefore, the objective of this study was to investigate the residual BNI effect of a converted long-term Bh pasture on subsequent maize (Zea mays L.) cropping, where a long-term maize monocrop field (M) served as control. Methods Four levels of N fertilizer rates (0, 60,120 and 240 kg N ha−1) and synthetic nitrification inhibitor (dicyandiamide) treatments allowed for comparison of BNI effects, while 15N labelled micro-plots were used to trace the fate of applied fertilizer N. Soil was incubated to investigate N dynamics. Results A significant maize yield increase after Bh was evident in the first year compared to the M treatment. The second cropping season showed an eased residual effect of the Bh pasture. Soil incubation studies suggested that nitrification was significantly lower in Bh soil but this BNI declined one year after pasture conversion. Plant N uptake was markedly greater under previous Bh compared with M. The N balance of the 15N micro-plots revealed that N was derived mainly (68–86%) from the mineralized soil organic N pool in Bh while plant fertilizer N recovery (18–24%) was not enhanced. Conclusions Applied N was strongly immobilized due to long-term root turnover effects, while a significant residual BNI effect from Bh prevented re-mineralized N from nitrification resulting in improved maize performance. However, a significant residual Bh BNI effect was evident for less than one year only.

The application of leguminous green manure (GM) can enhance the soil inorganic phosphorus (Pi) pool, offering considerable benefits for crop cultivation in slightly and moderately saline-alkali soils. To optimize its agronomic potential, systematic and science-based fertilization strategies are required. In this study, we researched the changes in the content, movement distance, and accumulation of Pi fractions at the GM microsites in coastal saline-alkali soils of differing salinity levels (slightly vs. moderately) following the application of Sesbania GM at two rates (30 and 60 t ha−1) over 14- and 28-day incubation periods. The results indicated that GM application significantly (p < 0.05) increased the accumulation of all Pi fractions—including aluminum-bound phosphorus (Al-P), iron-bound phosphorus (Fe-P), occluded phosphorus (O-P), and forms of calcium-bound Pi (Ca-P: Ca2-P, Ca8-P, and Ca10-P)—at the manure microsite, with the magnitude of increase declining with distance from the manure site. Further analysis revealed positive correlations between GM rate, two incubation periods and Pi-fraction movement distance, indicating that the observed effects were significantly influenced by incubation period, GM rate, and soil salinity-alkalinity. While temporal dynamics governed the rates of Pi movement and transformation, elevated salinity-alkalinity partially inhibited these processes. This study provides practical insights for improving GM utilization efficiency on saline-alkali soils. These results support optimized GM application to enhance P efficiency and reduce fertilizer reliance in saline systems.

Background: As the first pathway-specific enzyme in carotenoid biosynthesis, phytoene synthase (PSY) is a prime regulatory target. This includes a number of biotechnological approaches that have successfully increased the carotenoid content in agronomically relevant non-green plant tissues through tissue-specific PSY overexpression. We investigated the differential effects of constitutive AtPSY overexpression in green and non-green cells of transgenic Arabidopsis lines. This revealed striking similarities to the situation found in orange carrot roots with respect to carotenoid amounts and sequestration mechanism. Methology/Principal Findings: In Arabidopsis seedlings, carotenoid content remained unaffected by increased AtPSY levels although the protein was almost quantitatively imported into plastids, as shown by western blot analyses. In contrast, non-photosynthetic calli and roots overexpressing AtPSY accumulated carotenoids 10 and 100-fold above the corresponding wild-type tissues and contained 1800 and 500 µg carotenoids per g dry weight, respectively. This increase coincided with a change of the pattern of accumulated carotenoids, as xanthophylls decreased relative to β-carotene and carotene intermediates accumulated. As shown by polarization microscopy, carotenoids were found deposited in crystals, similar to crystalline-type chromoplasts of non-green tissues present in several other taxa. In fact, orange-colored carrots showed a similar situation with increased PSY protein as well as carotenoid levels and accumulation patterns whereas wild white-rooted carrots were similar to Arabidopsis wild type roots in this respect. Initiation of carotenoid crystal formation by increased PSY protein amounts was further confirmed by overexpressing crtB, a bacterial PSY gene, in white carrots, resulting in increased carotenoid amounts deposited in crystals. Conclusions: The sequestration of carotenoids into crystals can be driven by the functional overexpression of one biosynthetic enzyme in non-green plastids not requiring a chromoplast developmental program as this does not exist in Arabidopsis. Thus, PSY expression plays a major, rate-limiting role in the transition from white to orange-colored carrots.

The rumen microbiome plays a fundamental role in all ruminant species, it is involved in health, nutrient utilization, detoxification, and methane emissions. Methane is a greenhouse gas which is eructated in large volumes by ruminants grazing extensive grasslands in the tropical regions of the world. Enteric methane is the largest contributor to the emissions of greenhouse gases originating from animal agriculture. A large variety of plants containing secondary metabolites [essential oils (terpenoids), tannins, saponins, and flavonoids] have been evaluated as cattle feedstuffs and changes in volatile fatty acid proportions and methane synthesis in the rumen have been assessed. Alterations to the rumen microbiome may lead to changes in diversity, composition, and structure of the methanogen community. Legumes containing condensed tannins such as Leucaena leucocephala have shown a good methane mitigating effect when fed at levels of up to 30–35% of ration dry matter in cattle as a result of the effect of condensed tannins on rumen bacteria and methanogens. It has been shown that saponins disrupt the membrane of rumen protozoa, thus decreasing the numbers of both protozoa and methanogenic archaea. Trials carried out with cattle housed in respiration chambers have demonstrated the enteric methane mitigation effect in cattle and sheep of tropical legumes such as Enterolobium cyclocarpum and Samanea saman which contain saponins. Essential oils are volatile constituents of terpenoid or non-terpenoid origin which impair energy metabolism of archaea and have shown reductions of up to 26% in enteric methane emissions in ruminants. There is emerging evidence showing the potential of flavonoids as methane mitigating compounds, but more work is required in vivo to confirm preliminary findings. From the information hereby presented, it is clear that plant secondary metabolites can be a rational approach to modulate the rumen microbiome and modify its function, some species of rumen microbes improve protein and fiber degradation and reduce feed energy loss as methane in ruminants fed tropical plant species.

Grassland pastures are crucial for the global food supply through their milk and meat production; hence, forage species monitoring is essential for cattle feed. Therefore, knowledge of pasture above-ground canopy features help understand the crop status. This paper finds how to construct machine learning models to predict above-ground canopy features in Brachiaria pasture from ground truth data (GTD) and remote sensing at larger (satellite data on the cloud) and smaller (unmanned aerial vehicles (UAV)) scales. First, we used above-ground biomass (AGB) data obtained from Brachiaria to evaluate the relationship between vegetation indices (VIs) with the dry matter (DM). Next, the performance of machine learning algorithms was used for predicting AGB based on VIs obtained from ground truth and satellite and UAV imagery. When comparing more than twenty-five machine learning models using an Auto Machine Learning Python API, the results show that the best algorithms were the Huber with R2 = 0.60, Linear with R2 = 0.54, and Extra Trees with R2 = 0.45 to large scales using satellite. On the other hand, short-scale best regressions are K Neighbors with an R2 of 0.76, Extra Trees with an R2 of 0.75, and Bayesian Ridge with an R2 of 0.70, demonstrating a high potential to predict AGB and DM. This study is the first prediction model approach that assesses the rotational grazing system and pasture above-ground canopy features to predict the quality and quantity of cattle feed to support pasture management in Colombia.

More than one-quarter of the world’s greenhouse gas emissions come from agriculture, forestry, and land-use change. As with other sectors of the economy, agriculture should also contribute to meeting countries’ emission reduction targets. Transformation of agriculture to low-carbon food systems requires much larger investments in low emission development options from global climate finance, domestic budgets, and the private sector. Innovative financing mechanisms and instruments that integrate climate finance, agriculture development budgets, and private sector investment can improve and increase farmers’ and other value chain actors’ access to finance while delivering environmental, economic, and social benefits. Investment cases assessed in this study provide rich information to design and implement mitigation options in agriculture through unlocking additional sources of public and private capital, strengthening the links between financial institutions, farmers, and agribusiness, and coordination of actions across multiple stakeholders. These investment cases expand support for existing agricultural best practices, integrate forestry and agricultural actions to avoid land-use change, and support the transition to market-based solutions.

Modern intensively managed pastures that receive large external nitrogen (N) inputs account for high N losses in form of nitrate (NO3–) leaching and emissions of the potent greenhouse gas nitrous oxide (N2O). The natural plant capacity to shape the soil N cycle through exudation of organic compounds can be exploited to favor N retention without affecting productivity. In this study, we estimated the relationship between biological nitrification inhibition (BNI), N2O emissions and plant productivity for 119 germplasm accessions of Guineagrass ( Megathyrsus maximus ), an important tropical forage crop for livestock production. This relation was tested in a greenhouse experiment measuring BNI as (i) rates of soil nitrification; (ii) abundance of ammonia-oxidizing bacteria (AOB) and archaea (AOA); and (iii) the capacity of root tissue extracts to inhibit nitrification in vitro . We then measured N2O emissions, aboveground biomass and forage nutrition quality parameters. Reductions on nitrification activity ranging between 30 and 70% were found across the germplasm collection of M. maximus . Accessions with low nitrification rates showed a lower abundance of AOB as well as a reduction in N2O emissions compared to accessions of high nitrification rates. The BNI capacity was not correlated to N uptake of plants, suggesting that there may be intraspecific variation in the exploitation of different N sources in this grass species. A group of accessions (cluster) with the most desirable agronomic and environmental traits among the collection was identified for further field validation. These results provide evidence of the ability of M. maximus to suppress soil nitrification and N2O emissions and their relationship with productivity and forage quality, pointing a way to develop N conservative improved forage grasses for tropical livestock production.

Curve squeal is a highly disturbing tonal noise produced by railway vehicles on tight curves, primarily attributed to lateral sliding at the wheel–rail interface. An essential step to estimate curve squeal noise levels is to determine the nonlinear self-sustained vibrations, for which time integration is a commonly used method. However, although it is known that the initial conditions affect the solutions obtained with time integration, their impact on the limit cycles is often overlooked. This study investigates this aspect for a curve squeal model based on falling friction and a modal reduction of the wheel and provides some insights on the mode competition phenomena and the nature of the final limit cycles obtained. The paper first details the curve squeal model, stability analysis, as well as the initial condition derivation, and then discusses the time integration and limit cycle results in both time and frequency domains. The results reveal two primary families of limit cycles that can be obtained for both types of initial conditions. The cases where stationary vibrations result in a quasi-periodic regime converge to a unique limit cycle which displays three fundamental frequencies corresponding to specific wheel modes, plus harmonic interactions among them.

The capacity of several plant species or landraces to inhibit nitrification in soil (biological nitrification inhibition, BNI) has been assessed in certain tropical pastures. These assessments are commonly based on potential net nitrification rates, which do not differentiate between gross nitrification and other processes that may reduce the amount of nitrate in soil. In a greenhouse experiment using two genotypes of Urochloa humidicola with contrasting BNI capacity in vitro, we evaluated gross N transformation rates before and after (7 and 21 days) N fertilization, while periodically measuring N2O emissions. Gross nitrification rates (in fact gross nitrate production assessed by pool dilution technique) were comparable in both genotypes and were low in comparison to strong microbial NH4+ immobilization. The N2O emissions were higher in pots with low-BNI plants. The discrepancy between the potential net nitrification rates assessed in laboratory assays (higher in low-BNI plants) and gross nitrification in pot or field experiments (no differences between genotypes) can be attributed to the out-competition of ammonia oxidizers by plant N uptake and ammonia immobilizing heterotrophic microbes, resulting in low nitrification under conditions where growing plants are present. This study confirmed the capacity of certain U. humidicola genotypes to reduce N2O emissions but warrants further investigation of the underlying mechanisms. It also questions the relevance of BNI in the rhizosphere of this plant species as other mechanisms (rather than the inhibition of gross nitrification) seem to be more important in maintaining low-nitrate soil environments in soil–plant systems of U. humidicola.

Biological nitrification inhibition (BNI) has been considered a plant strategy to increase N use efficiency by reducing N losses via N2O emissions or nitrate leaching. However, recent studies have revealed no difference in gross nitrate production among Urochloa humidicola genotypes with previously described high- and low-BNI capacity and pointed towards a crucial role for microbial N immobilization. In the current greenhouse study, we compared the 15 N acquisition by two U. humidicola genotypes (with high- and low-BNI capacity) and their soil-associated microorganisms at four points in time after fertilization (50 kg N ha−1). Soil microorganisms slightly out-competed both genotypes during the first 24 h after fertilization, and microorganisms associated with high-BNI genotype immobilized more N than microbes associated with low-BNI plants. Nevertheless, by the end of the experiment, low-BNI plant genotype had acquired more 15 N, despite higher to N2O emissions. Furthermore, higher 15 N root-to-shoot transfer was observed in low-BNI plants, potentially indicating higher contribution of nitrate to plant N uptake. In conclusion, our results confirm higher importance of microbial N immobilization in high-BNI genotypes, at least in the short-term. However, this did not result in higher N uptake by the high BNI genotype during the first 3 weeks after fertilization as could be expected. Long-term field studies are required to better understand the implications of direct (BNI sensu stricto) and indirect mechanisms (including differences in rhizosphere microbial biomass, activity and composition between high- and low-BNI genotypes), processes on plant N use efficiency, N storage in soil, and N losses to the environment.