Maize Silage Research Articles

Can hydroponic forage affect the chemical and sensory properties of PDO buffalo Mozzarella cheese?

The aim of this study was to evaluate the effect of hydroponic barley forage in the diets of lactating Italian Mediterranean buffaloes on Mozzarella cheese chemical and sensory properties. Thirty‐six buffaloes were evenly assigned to three groups: control (C) with standard maize silage‐based ration, and low hydroponic (LH) and high hydroponic (HH) barley forage substitution for 50% and 100% of maize silage, respectively. HH Mozzarella had lower hardness, reduced saturated fatty acids, increased oleic and α‐linolenic fatty acids. Hydroponic forage could be an innovative system for sustainable livestock production with a positive impact on the Mozzarella cheese improving its nutritional value.

Identification of metabolic and protein markers representative of the impact of mild nitrogen deficit on agronomic performance of maize hybrids

IntroductionA better understanding of the physiological response of silage maize to a mild reduction in nitrogen (N) fertilization and the identification of predictive biochemical markers of N utilization efficiency could contribute to limit the detrimental effect of the overuse of N inputs.ObjectivesWe integrated phenotypic and biochemical data to interpret the physiology of maize in response to a mild reduction in N fertilization under agronomic conditions and identify predictive leaf metabolic and proteic markers that could be used to pilot and rationalize N fertilization.MethodsEco-physiological, developmental and yield-related traits were measured and complemented with metabolomic and proteomic approaches performed on young leaves of a core panel of 29 European genetically diverse dent hybrids cultivated in the field under non-limiting and reduced N fertilization conditions.ResultsMetabolome and proteome data were analyzed either individually or in an integrated manner together with eco-physiological, developmental, phenotypic and yield-related traits. They allowed to identify (i) common N-responsive metabolites and proteins that could be used as predictive markers to monitor N fertilization, (ii) silage maize hybrids that exhibit improved agronomic performance when N fertilization is reduced.ConclusionsAmong the N-responsive metabolites and proteins identified, a cytosolic NADP-dependent malic enzyme and four metabolite signatures stand out as promising markers that could be used for both breeding and agronomic purposes.

Environment, Soil, and Digestate Interaction of Maize Silage and Biogas Production

In this study are presented the possibilities of using maize silage for biogas production. An experiment with maize silage took place over three years (2016–2018) in two localities, Ilandža, Alibunar municipality (L1—Locality 1) and Dolovo (L2—Locality 2), Serbia, and using two variants: a control with no digestate (C) and a variant with digestate, which was organic manure from biogas facilities (AD). In the AD variant, 50 t ha−1 of digestate was introduced into the soil just before sowing the maize. The following traits were examined: plant height (PH), biomass yield (BMY), biogas yield (BGY), and methane yield (MY). The effects of the studied factors (year, fertilization, and locality) on the biogas yield were significant (p < 0.5). The most favorable year for biogas production was 2016 (207.95 m3 ha−1), while the highest values of maize plant height, biomass, and methane yield were recorded in 2018 (2.48 m, 51.15 t ha−1 dry matter, and 258.25 m3 ha−1). The digestate exerted a significant influence (p < 0.5) on the values of all the tested maize parameters in all three experimental years. The biomass yield was positively associated with the plant height, biogas, and methane yield (r = 0.62 *; r = 0.70 *; r = 0.81 **) and positively but nonsignificantly associated with temperature (r = 0.42) and precipitation (r = 0.12). The application of the digestate before sowing improves the anaerobic digestion of maize silage and biogas production.

Robust methane production from anaerobic digestion of maize silage: Feeding control using sliding mode control strategy with Anaerobic Digestion Model N°01

This paper introduces a robust control approach based on the Sliding Mode Control (SMC) strategy for the AD process. We use the Anaerobic Digestion Model N°01 (ADM1), the most detailed and comprehensive model for AD, as a virtual AD plant. The proposed control scheme is derived from a reduced model. This control law uses the state variables of the reduced AM2HN model as well as the stoichiometric and kinetic parameters. An interface block between the ADM1 and AM2HN state variables has been designed in a closed loop. The performance of SMC has been enhanced by the use of a low-pass filter, which completely eliminates chattering and provides smooth dilution rates (chatter-free) while rapidly reaching the target methane production (in less than 5 days) in a noisy environment.

Maize intercropped with Panicum maximum cultivars and Pigeon pea improves silage yield and quality

Integrated systems are efficient technologies used for diversifying production and promoting agricultural sustainability. The benefits of double intercropping are well-established in research. With advancements in sustainable food production technology, some studies have explored triple intercropping by adding legumes. However, triple intercropping methods must be comprehensively understood. This study aimed to evaluate the production of dry mass, fermentation profile, and nutritive values of silage from maize based intercropping. The experiment was conducted in the field, in Instituto Federal Goiano, Campus Rio Verde, State of Goiás, Brazil, where we assessed silage production and quality in monoculture and intercropping systems, in a randomized block complete design with three replications. We evaluated 8 treatments, consisting of silage from: maize monoculture; Tamani guinea grass monoculture; Quênia guinea grass monoculture; Zuri guinea grass monoculture; Pigeon pea monoculture; maize + Tamani guinea grass + Pigeon pea; maize + Quênia guinea grass + Pigeon pea and maize + Zuri guinea grass + Pigeon pea. The results showed that maize silage intercropped with cultivars of Panicum maximum (Tamani, Quênia and Zuri guinea grasses) and Pigeon pea increased silage mass production by 37.8% and the crude protein content at 25.1% compared with that of the monoculture maize silage. It also improved the fermentation characteristics of silage, reducing 5.1% of pH, 32.5% of buffering capacity, 28.9% of ammoniacal nitrogen in total nitrogen, 15.7% of effluent production, and 20.0% of dry matter losses, compared with those of grass and legume silage in monoculture. Thus, the silage produced by the triple intercropping proved to be an efficient technique for sustainable forage production.

The Application of a Foliar Spray Containing Methylobacterium symbioticum Had a Limited Effect on Crop Yield and Nitrogen Recovery in Field and Pot-Grown Maize.

In this study, the effectiveness of an inoculant containing a nitrogen (N)-fixing microorganism (Methylobacterium symbioticum) was evaluated on maize (Zea mays L.) grown both in the field (silage maize) and in pots over two years (2021 and 2022). The field trial included the following two treatments: with (Yes) and without (No) the inoculant. The pot experiment was designed as a factorial arrangement with two factors: the application of the inoculant (Yes and No) and N applied to the soil (0, 0.4, 0.8, and 1.6 g pot-1). In the field, total dry matter yield (DMY) did not differ significantly between treatments, although the average DMY was higher in the inoculant treatment. In pots, the total DMY varied significantly across all N rates but was only significantly affected by the inoculant application in 2022. N fixation estimates in the field were 58.8 and 14.5 kg ha-1 for 2021 and 2022, respectively, representing 23.7% and 9.1% of the N recovered in the aboveground plant parts. In pots, the estimated fixed N values were -49.2 and 199.2 mg pot-1 in 2021 and 2022, respectively, which corresponded to -5.2% and 18.5% of the N found in the aboveground plant parts. Considering the average values obtained across the four cultivation conditions, there was a positive outcome for the treated plants. However, these values cannot be considered significant when compared to nitrogen removal in maize crops. A commercial product should provide an unequivocal and quantitatively relevant contribution to plant nutrition, which did not appear to be the case. Thus, for this inoculant to provide reliable guarantees of positive outcomes for farmers and become a useful tool in promoting more sustainable agriculture, further studies appear necessary. These studies should aim to determine in which crops and under what cultivation conditions the application of the inoculant is truly effective in enhancing N fixation and improving crop productivity.

Influence of Ensiling Timing and Inoculation on Whole Plant Maize Silage Fermentation and Aerobic Stability (Preliminary Research)

Despite efforts to prevent atypical ensiling conditions, such as delayed ensiling or sealing, these issues frequently occur in practice. This study aimed to investigate the effects of delayed ensiling (forage held for 24 h) and sealing, along with inoculation using a blend of Lentilactobacillus buchneri and Lactococcus lactis, on the characteristics of the resulting silages. Whole-plant maize (Zea mays L.) was treated with or without a commercial inoculant and ensiled (36% dry matter) for 60 days in 3.0 L glass containers. The forage was either ensiled immediately or subjected to a 24 h delay before ensiling. During the delay, the forage was either covered or left uncovered. Each treatment was replicated five times. All data were analyzed using the MIXED procedure of SAS statistical software (version 9.4; SAS Institute Inc., Cary, NC, USA). Delaying the ensiling process by 24 h worsens fermentation parameters, significantly increases dry matter (DM) losses (p < 0.01), and significantly reduces aerobic stability and the hygienic quality of the silage (p < 0.01), as evidenced by higher concentrations of undesirable fermentation products and elevated yeast and mold counts. The inoculation has a significant impact on both forage before ensiling and the characteristics of the resulting silage. Maize forage treated with inoculant showed a lower temperature increase by 8.2–8.1 °C (p < 0.01) when delayed for 24 h before ensiling. In silages, it also resulted in a reduced pH (p < 0.01); increased concentrations of lactic acid; acetic acid; and 1,2-propanediol (p < 0.01); and decreased levels of negative fermentation indicators such as ammonia-N, alcohols, and butyric acid (p < 0.01) During both the fermentation and aerobic exposure periods, inoculated silages exhibited up to 36% and 2.6 times lower (p < 0.01) dry matter loss, while suppressing the growth of yeasts and molds by up to 2.6 and 3.1 times (p < 0.01), respectively, compared to non-inoculated silages. The results of this study support the recommendation to minimize the duration of aerobic exposure of fresh forage during silo filling and to use LAB-based inoculants.

The Effects of Corn Silage and Sunflower Silage and Their Mixtures at Different Levels on the Fattening Performance of Kıvırcık Lambs

Maize silage is widely used in the nutrition of ruminants worldwide. Nevertheless, maize is expensive and difficult to grow in cold and arid climates. To investigate the effects of feeding pure maize silage and different mixtures of maize and sunflower silages on the fattening performance of lambs. In the study, 40 Kıvırcık male lambs aged 2.5-3 months and with an average live weight of 23-25 kg were used as the animal material. The experiment was carried out for 56 days in a semi-open barn. In accordance with the experimental design, animals were divided into 5 different silage groups (100 maize silage, 75 maize silage+25 sunflower silage, 50 maize silage+50 sunflower silage, 25 maize silage+75 sunflower silage, 100% sunflower silage), so that there would be 8 lambs in each group. The lambs were housed in individual compartments during the experiment and fed individually. Silages were given ad libitum, and additional 700, 900, and 1,400 g concentrated feed was given daily between the 0th and 21st, 21st and 42nd, and 42nd and 56th days, respectively. During the fattening period, the values of live weight, daily live weight gain, feed consumption, and feed conversion ratio were determined. The differences among the live weight values of different silage groups during the trial period were found to be not significant (p>0.05), and the values obtained at the end of 8 weeks varied between 35.94 and 37.44 kg. The silage consumption of lambs fed different silage types showed significant differences (p

The Economic Efficiency of Micro Biogas Plants: A Sustainable Energy Solution in Slovenia—Case Study

This paper presents a simulation model for determining the most suitable type of microbiogas plant for small local communities on Slovenian farms, focusing on the efficient processing of organic waste. This model uses various input parameters, including different types and quantities of slurry and corn silage. Four different scenarios were developed to represent potential plant sizes, each evaluated using key economic indicators: net present value, breakthrough price, and internal rate of return. A scenario sensitivity analysis was conducted to assess the effects of changes in investment costs, fluctuations in energy prices, and the addition of corn silage to the anaerobic digestion process. The results highlight significant differences in economic viability across the scenarios, with some demonstrating positive financial outcomes and shorter payback periods and others indicating potential financial risks and longer recovery times under certain conditions. The analysis suggests that smaller micro biogas plants may struggle to achieve profitability without optimizing input ratios or reducing costs, whereas larger plants show more favorable economic indicators, provided certain conditions are met. Furthermore, the economic efficiency improves when adding maize silage to the fermentor mixture.

Translating 2D-Chromatographic Fingerprinting to Quantitative Volatilomics: Unrevealing Compositional Changes in Maize Silage Volatilome for Robust Marker Discovery.

This study examines the complex volatilome of maize silage, both with and without commercial heterolactic strain inoculation, conserved for 100 days, using quantitative volatilomics. Chemical classes linked to microbial metabolism were analyzed across a concentration range from 10 μg g-1 to 1 ng g-1. A reference method using comprehensive two-dimensional gas chromatography (GC × GC) and time-of-flight mass spectrometry (TOF MS) with loop-type thermal modulation (TM) was translated to a differential-flow modulation (FM) platform with parallel MS and flame ionization detector (FID) detection. With translation, the original method's analyte elution order and resolution are preserved. The new method allowed for accurate quantification using multiple headspace solid-phase microextraction (MHS-SPME) and FID-predicted relative response factors (RRFs). Both methods showed comparable discriminatory power with FM GC × GC-MS/FID achieving satisfactory quantification accuracy without external calibration. Analysis of 98 volatiles provided insights into silage fermentation, supporting marker discovery and correlations with silage quality and stability.

Transforming the feeding regime towards low-input increases the environmental impact of organic milk production on a case study farm in central germany

Abstract Purpose Despite the direct effect of the feeding regime on the environmental impacts of dairy farming systems, its level of intensity, particularly in organic systems, has rarely been investigated. This study compares the environmental impact of a high-input feeding regime with a grassland-based, low-input feeding regime scenario within an organic milk production system conducted on Gladbacherhof, the research farm of Justus Liebig University Giessen, in Central Germany. Methods An integrated Life Cycle Assessment (LCA) analysis was performed from a cradle-to-farm gate perspective to quantify five environmental impacts, namely Global Warming (GW), Non-Renewable Energy Use (NREU), Land Use (LU), Terrestrial Acidification (TA), and Freshwater Eutrophication (FE). All agronomic data of the Gladbacherhof research farm, averaged over the years 2010–2017, were included. When not directly measured on the farm, ecoinvent data were included. Results and discussion Contrary to our hypothesis, the results suggest that a grassland-based low-input system has a higher environmental impact as compared to a high-input system for each of the five impact categories when using fat and protein-corrected milk (FPCM) as the functional unit. A 50% reduction in concentrates and exclusion of maize silage from the feed ration in the modelled low-input production system lead to a 20% drop in milk yield. To balance the energy content in low-input feeding ration, longer grazing period and higher amount of hay, alfalfa, and grass silage are required. This in turn results in higher emissions from enteric fermentation, manure management, and feed production and hence in higher environmental impact, particularly for GW, TA, and FE. Conclusions This study is one of the few that directly explores the environmental impact of feeding intensity in an organic milk production system. Nevertheless, there is a lack of research on consolidated emission factors for several greenhouse gas (GHG) sources in organic livestock and cropping systems to perform more robust carbon footprint calculations that comply with the Intergovernmental Panel on Climate Change (IPCC) Tier 3 GHG reporting guidelines. To generalize the results at the regional or national scale, direct comparisons with a larger number of organic farms representative of high-input and low-input intensities are still essential.

Integrated rather than organic farming history facilitates soil nitrogen turnover and N2O reduction in a green rye – silage maize cropping sequence

AbstractSoil gross mineral N production and consumption processes are crucial regulators of plant productivity and N loss from croplands. Substituting synthetic fertilizers by integrating legumes in cultivation systems is common in organic farming, but research on its long-term impact on dynamics of gross soil N transformation and associated environmental N loss is scarce. In particular, studies at a temporal resolution that allows for a mechanistic understanding of long-term effects of organic farming are missing. Therefore, we determined gross N turnover rates of ammonification, nitrification, and ammonium and nitrate immobilization at monthly temporal resolution during a full green rye-maize cropping sequence. Measurements were carried out at sites with same pedo-climatic background but organic farming (OF) and integrated farming (IF) history. During green rye growing, N turnover rates for OF and IF were low and not significantly different, likely owing to low temperatures. During silage maize growing, IF exhibited significantly higher average N turnover rates of 1.86, 4.46, and 5.57 mg N kg⁻1 dry soil d⁻1 for gross ammonification, ammonium immobilization, and nitrate immobilization, respectively, compared to OF values of 1.11, 1.80, and 2.90 mg N kg⁻1 dry soil d⁻1. The significantly higher N turnover rates were likely due to higher soil organic C, N and microbial biomass which result from different long-term management practices. Especially the increased immobilization potential on the IF site contributed to significantly lower area-scaled N₂O emissions (1.45 vs. 4.36 kg N ha⁻1) during periods of high nitrification. This shows that for low SOC soils, integrated farming history with high C return enhances soil N cycling and reduces the risk of N losses in the form of N2O emission.

Hydroponic fodder as alternative feeds for ruminants to reduce ruminal methane emissions: an in vitro study

Malate, a precursor in the ruminal propionate production pathway, competes with methanogenesis for metabolic hydrogen, offering a way to reduce ruminal methane (CH4) production in ruminants. However, cost considerations hinder widespread use of malate in ruminant diets. An alternative approach involves utilizing transient malate levels generated during seed germination via the glyoxylate cycle. This study investigated the methane-mitigating potential of malate-containing hydroponic fodder. Fodder samples with peak malate concentrations from alfalfa, forage pea, Italian ryegrass, rye, soybean, triticale, and wheat during germination were subjected to in vitro rumen fermentation using the Hohenheim gas test. The basal diet of in vitro fermentation comprised 40% grass silage, 40% maize silage, 15% hay, and 5% concentrate on a dry matter basis, with nutritional characteristics including 42.1% neutral detergent fiber (NDF), 25.0% acid detergent fiber, 14.0% starch, 12.7% crude protein, and 3.5% ether extract (EE), on a dry matter basis. Experimental treatments were fodder inclusion involved replacing 20% of the basal diet (20R), and additionally, 100% replacement of the silages with alfalfa d 10 and rye d 9 (SR), the 2 high-malate fodders. Reductions in CH4 production were observed with soybean (20R, 6.7% reduction), alfalfa (20R, 6.6% reduction), and increased with rye (20R, 6.3% increase). In the setup replacing silages with high-malate fodders (SR), alfalfa decreased CH4 production (17.7%) but increased ammonia (174%), while rye increased CH4 production (35.8%). Organic matter digestibility increased with SR rye (12.6%). Marginal effects of dietary variables were analyzed in a Generalized Additive Model. A negative relationship between dietary malate content and CH4 production was observed, whereas dietary NDF and starch content were positive correlated with CH4 production. In conclusion, malate within the hydroponic fodder could potentially reduce CH4 emissions in ruminants. However, achieving sufficient efficacy requires high malate content. Additionally, use of hydroponic fodder may increase the risk of nitrogen emissions. Animal studies are required for further investigation.

The Effect of Humic Acid Supplementation on Selected Ruminal Fermentation Parameters and Protozoal Generic Distribution in Cows

The objective of this study was to examine the effect of humic acid (HA) supplementation on the rumen fermentation and protozoal community in the rumen. For this purpose, four ruminally cannulated Simmental cows were randomly assigned in a replicated 4 × 4 Latin square design experiment to study the effect of HA dietary supplementation on feed utilization, rumen fermentation, and protozoal community for 84 days. The basal diet (BD) was composed of meadow hay (68.2% of dry matter [DM]), maize silage (17% of DM), and granulated feed mixture (14.9% of DM). There were four treatments, including the BD without additives (control diet, H0), the BD supplemented with 50 g HA/cow/day (H50 treatment), the BD supplemented with 100 g HA/cow/day (H100 treatment), and the BD supplemented with 200 g HA/cow/day (H200 treatment). HA supplementation did not affect the total or individual volatile fatty acid concentrations, the total protozoa, or the ruminal pH. However, HA at the dosage of 50 g/cow/day increased the NH3-N concentration and fecal nitrogen compared to the control (p < 0.001). HA supplementation also significantly impacted the abundance of individual protozoal genera in the rumen. The results of this study suggest that HA has potential in ruminants as a natural feed additive and may play a role in nitrogen metabolism and stabilizing the protozoal community without adverse effects on rumen fermentation.

Rapid Lactic Acid Content Detection in Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging

Lactic acid content is a crucial indicator for evaluating maize silage quality, and its accurate detection is essential for ensuring product quality. In this study, a quantitative prediction model for the change of lactic acid content during the secondary fermentation of maize silage was constructed based on a colorimetric sensor array (CSA) combined with hyperspectral imaging. Volatile odor information from maize silage samples with different days of aerobic exposure was obtained using CSA and recorded by a hyperspectral imaging (HSI) system. Subsequently, the acquired spectral data were subjected to preprocessing through five distinct methods before being modeled using partial least squares regression (PLSR). The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to screen three color-sensitive dyes that are more sensitive to changes in lactic acid content of maize silage. To minimize model redundancy, three algorithms, such as competitive adaptive reweighted sampling (CARS), were used to extract the characteristic wavelengths of the three dyes, and the combination of the characteristic wavelengths obtained by each algorithm was used as an input variable to build an analytical model for quantitative prediction of the lactic acid content by support vector regression (SVR). Moreover, two optimization algorithms, namely grid search (GS) and crested porcupine optimizer (CPO), were compared to determine their effectiveness in optimizing the parameters of the SVR model. The results showed that the prediction accuracy of the model can be significantly improved by choosing appropriate pretreatment methods for different color-sensitive dyes. The CARS-CPO-SVR model had better prediction, with a prediction set determination coefficient (RP2), root mean square error of prediction (RMSEP), and a ratio of performance to deviation (RPD) of 0.9617, 2.0057, and 5.1997, respectively. These comprehensive findings confirm the viability of integrating CSA with hyperspectral imaging to accurately quantify the lactic acid content in silage, providing a scientific and novel method for maize silage quality testing.

Is the volatility of yields for major crops grown in Germany related to spatial diversification at county level?

Abstract Recent evidence suggests a stabilizing effect of crop diversity on agricultural production. However, different methods are used for assessing these effects and there is little systematic quantitative evidence on diversification benefits. The aim of this study was to assess the relationship between volatility of combined crop yields (denoted as standard deviation) and diversity (denoted as Shannon’s Evenness Index SEI) for standardized yield data of major crop species grown in Germany between 1977 and 2018 (winter wheat, winter barley, silage maize and winter rapeseed) at the county level. Portfolio theory was used to estimate the optimal crop area share for minimizing yield volatility. On average, results indicated a weak negative relationship between volatility and the SEI during the past decades for the case of Germany. Optimizing crop area shares for minimizing volatility reduced yield variance on average by 24 % but was associated with a decrease in SEI for most counties. This was related to the finding that the stability of individual species, i.e., barley and wheat, was more effective in reducing the volatility of combined yields than the asynchronous variation in annual yields among crops. Future studies might include an increased number of crop species and consider temporal diversification effects for a more realistic assessment of the relation between yield volatility and crop diversity and test the relationship in other regions and production conditions.

A comparative evaluation of maize silage quality under diverse pre-ensiling strategies.

Maize silage serves as a significant source of energy and fibre for the diets of dairy and beef cattle. However, the quality of maize silage is contingent upon several crucial considerations, including dry matter loss, fermentative profile, pH level, ammonia content, and aerobic stability. These aspects are influenced by a multitude of factors and their interactions, with seasonality playing a crucial role in shaping silage quality. In this study an open-source database was utilised to assess the impact of various pre-ensiling circumstances, including the diversity of the chemical composition of the freshly harvested maize, on the silage quality. The findings revealed that seasonality exerts a profound influence on maize silage quality. Predictive models derived from the composition of freshly harvested maize demonstrated that metrics were only appropriate for screening purposes when utilizing in-field sensor technology. Moreover, this study suggests that a more comprehensive approach, incorporating additional factors and variability, is necessary to better elucidate the determinants of maize silage quality. To address this, combining data from diverse databases is highly recommended to enable the application of more robust algorithms, such as those from machine learning or deep learning, which benefit from large data sets.

Greenhouse gas and volatile organic compound emissions of additive-treated whole-plant maize silage: part A—anaerobic fermentation period

BackgroundSilage emits climate- and environment-relevant gases during fermentation and feed-out periods. This trial aimed to determine the unknown carbon dioxide (CO2), methane, nitrous oxide, ethanol, and ethyl acetate emissions of constant maize silage material over both periods. The results will be published in two consecutive articles (Part A: anaerobic fermentation period, Part B: aerobic storage period).MethodsThe untreated control (CON) was compared with the chemical additive treatment (CHE; 0.5 g sodium benzoate and 0.3 g potassium sorbate per kg fresh matter) and the biological additive treatment (BIO; 108 colony-forming units (CFU) Lentilactobacillus buchneri and 107 CFU Lactiplantibacillus plantarum per kg fresh matter). Barrel silos (n = 4) were connected to gas bags to quantify gas formation during anaerobic fermentation (30 or 135 ensiling days). Glass jar silos (n = 12) were used for laboratory silage analysis.ResultsCHE produced significantly (p < 0.05) less gas (6.7 ± 0.3 L per kg dry matter ensiled material (kgDM) until ensiling day 14.0 ± 0.0) and ethanol (8.6 ± 1.5 mg kgDM–1) than CON did (8.5 ± 0.2 L kgDM–1 until ensiling day 19.5 ± 6.4; 12.2 ± 1.5 (mg ethanol) kgDM–1). BIO indicates prolonged gas formation (9.1 ± 0.9 L kgDM–1 until ensiling day 61.3 ± 51.9; 12.0 ± 2.1 mg kgDM–1). CO2 is the main component of the gas formed. All treatments formed methane and nitrous oxide in small quantities. CON emitted significantly more CO2eq emissions than BIO and less than CHE (p < 0.05). Additives had no effect on ethyl acetate gas emissions. For BIO, ethanol concentrations in the material (rS = 0.609, p < 0.05) and gas quantities (rS = 0.691, p < 0.05) correlate with ethyl acetate gas quantities. All the treatments exhibited decreasing gas and CO2 quantities, and the dry matter mass increased between ensiling days 14 and 30 (− 0.810 ≤ rS ≤ 0.442; p < 0.05 to p = 0.20).ConclusionSilage generates climate- and environmental-relevant gases during fermentation and silage additives affect this pattern. Gas formation exceeds the fixation potential, and the carbon footprint of silage fermentation is negative.Graphical

A comparison of climate drivers’ impacts on silage maize yield shock in Germany

Extreme weather events have become more frequent and severe with ongoing climate change, with a huge implication for the agricultural sector and detrimental effects on crop yield. In this study, we compare several combinations of climate indices and utilized the Least Absolute Shrinkage and Selection Operator (LASSO) to explain the probabilities of substantial drops in silage maize yield (here defined as “yield shock” by using a 15th percentile as threshold) in Germany between 1999 and 2020. We compare the variable importance and the predictability skill of six combinations of climate indices using the Matthews Correlation Coefficient (MCC). Finally, we delve into year-to-year predictions by comparing them against the historical series and examining the variables contributing to high and low predicted yield shock probabilities. We find that cold conditions during April and hot and/or dry conditions during July increase the chance of silage maize yield shock. Moreover, a combination of simple variables (e.g. total precipitation) and complex variables (e.g. cumulative cold under cold nights) enhances predictive accuracy. Lastly, we find that the years with higher predicted yield shock probabilities are characterized mainly by relatively hotter and drier conditions during July compared to years with lower yield shock probabilities. Our findings enhance our understanding of how weather impacts maize crop yield shocks and underscore the importance of considering complex variables and using effective selection methods, particularly when addressing climate-related events.

Power Predicting for Power Take-Off Shaft of a Disc Maize Silage Harvester Using Machine Learning

Power Predicting for Power Take-Off Shaft of a Disc Maize Silage Harvester Using Machine Learning