Sugar Beet Research Articles

Response of some sugar beet (Beta vulgaris L) varieties to different harvest dates under Middle Egypt conditions.

Response of some sugar beet (Beta vulgaris L) varieties to different harvest dates under Middle Egypt conditions.

DEVELOPMENT OF TECHNOLOGY OF PECTIN-CONTAINING GALETS WITH LONG SHELF LIFE

The aim of the work was to study the effect of pectin concentrate from sugar beet of the «Ardan» variety on the quality of galets made from wheat flour of the first grade. The obtained research results show that the use of pectin concentrate when kneading dough from wheat flour of the first grade improves the organoleptic and physico-chemical quality indicators of galets in comparison with samples without pectin concentrate. The best quality of galets was achieved by applying 10% pectin concentrate to the weight of wheat flour of the first grade. The study of the nutritional value and safety of galets determines the expediency and validity of the use of new types of raw materials in the production technology of galets. It was found that the nutritional and biological value of the developed galets is not inferior to the control sample, and the products obtained comply with the safety requirements of TR CU 021/2011 Technical Regulations of the Customs Union "On food safety". Based on the results obtained, a technological scheme for the production of galets using beetroot pectin concentrate is proposed. The use of low-esterified pectin in the production of galets open up wide prospects for the creation of biologically complete fundamentally new safe food products with pronounced functional properties.

Evaluating Rhizobacterial Antagonists for Controlling Cercospora beticola and Promoting Growth in Beta vulgaris.

Cercospora beticola Sacc. is an ascomycete pathogen that causes Cercospora leaf spot in sugar beets (Beta vulgaris L.) and other related crops. It can lead to significant yield losses if not effectively managed. This study aimed to assess rhizosphere bacteria from sugar beet soil as a biological control agent against C. beticola and evaluate their effect on B. vulgaris. Following a dual-culture screening, 18 bacteria exhibiting over 50% inhibition were selected, with 6 of them demonstrating more than 80% control. The bacteria were identified by sequencing the 16S rRNA gene, revealing 12 potential species belonging to 6 genera, including Bacillus, which was represented by 4 species. Additionally, the biochemical and molecular properties of the bacteria were characterized in depth, as well as plant growth promotion. PCR analysis of the genes responsible for producing antifungal metabolites revealed that 83%, 78%, 89%, and 56% of the selected bacteria possessed bacillomycin-, iturin-, fengycin-, and surfactin-encoding genes, respectively. Infrared spectroscopy analysis confirmed the presence of a lipopeptide structure in the bacterial supernatant filtrate. Subsequently, the bacteria were assessed for their effect on sugar beet plants in controlled conditions. The bacteria exhibited notable capabilities, promoting growth in both roots and shoots, resulting in significant increases in root length and weight and shoot length. A field experiment with four bacterial candidates demonstrated good performance against C. beticola compared to the difenoconazole fungicide. These bacteria played a significant role in disease control, achieving a maximum efficacy of 77.42%, slightly below the 88.51% efficacy attained with difenoconazole. Additional field trials are necessary to verify the protective and growth-promoting effects of these candidates, whether applied individually, combined in consortia, or integrated with chemical inputs in sugar beet crop production.

Harmonized European Union subnational crop statistics can reveal climate impacts and crop cultivation shifts

Abstract. The availability of coherent time series of crop statistics is essential for better analyzing the past, understanding the present, and predicting future trends in yield, area, and production. Importantly, such data also underpin assessments and subsequent policy actions that can shape future food systems that are more resilient in the face of climate change and that are sustainable in terms of resource use efficiency. In the European Union (EU), there currently is no legal obligation for EU countries to provide subnational crop statistics. However, such data could improve in-season crop forecasts, climate change impacts and adaption need assessments, and evaluation of agri-environmental schemes. The dataset described in this paper includes a harmonized collection of subnational crop statistics on area, production, and yield, collected for the EU from National Statistical Institutes (NSIs) and the EUROSTAT REGIO database – subnational crop statistics voluntarily contributed by EU countries. The crops considered are wheat (including soft and durum wheat), barley (including winter and spring barley), grain maize, sunflower, and sugar beet. All data are harmonized towards the hierarchical structure of the EUROSTAT legend and the regional classification of NUTS (Nomenclature of Territorial Units for Statistics) version 2016, to provide coherent time series. A total of 344 282 records is presented here (115 974 for wheat, 122 705 for barley, 35 274 for grain maize, 34 916 for sugar beet, and 35 413 for sunflower) for a total of 961 regions in 27 EU countries. Statistics are reported from 1975 to 2020, with a median time-span range of 21 years. A flagging system details, for each data record, information on data sources, processing steps, and quality-checking results. This includes consistency checks between reported values for area, yield and production, identification of null values, missing and calculated data, information on crop legend matching, and NUTS versioning. We illustrate the value of this dataset by analyzing impacts on crops and production zone shifts in Europe due to climatic and economic factors. Recommendations and future developments of collecting subnational statistics at the EU level are briefly discussed. The dataset is accessible with European Commission Authentication Service (ECAS) login at https://doi.org/10.2905/685949ff-56de-4646-a8df-844b5bb5f835 (Ronchetti et al., 2023b).

Composition of the weed flora in sugar beet cultivation in Germany – nationwide trials 1995–2022

Long-term data from 449 herbicide trials across Germany from 1995–2022 were used to characterise the weed composition in sugar beet cultivation. The assessments of 1782 untreated control plots showed local weed species composition and weed pressure. The most common weeds were Chenopodium album (82.3% of all plots), Polygonum convolvulus (52.2%) and Galium aparine (25%). The average number of weed species in the field trials decreased from 4.9 in 1995 to 2.6 in 2022, significantly influenced by trial location and year. The occurrence of the most frequent weeds has also changed. C. album and P. convolvulus increased while G. aparine and Matricaria chamomilla decreased. Possible reasons for these changes are different tillage systems and intensities as well as changes in crop rotation with decreased crop diversity. Herbicide treatments and different active ingredients also affect the occurrence and proportion of weeds. The trial sites were assigned to clusters accounting for climate attributes and soil properties to identify regional differences in weed infestation. Regions with low soil quality, high temperatures and low precipitation had higher weed diversity, presumably due to low crop cover and, thus, lower weed suppression. The proportion of C. album was very high in all regions because it can grow under a wide range of environmental conditions. For P. convolvulus, significant regional differences existed in its proportion of total weed infestation. Its importance was lower in regions with poorer soils.

Bioethanol production from dilute acid hydrolysis of cassava peels, sugar beet pulp, and green macroalgae (Ulva lactuca)

This study presents the characterization and application of different pretreatment possibilities to optimize simple carbohydrate production from representative feedstock, followed by ethanol production through optimized saccharification steps using suitable microorganisms. Total soluble carbohydrates and carbohydrate yield were evaluated using dilute acid hydrolysis of biomass and reference materials (starch and cellulose) under different conditions. To explore two-factor interactions, the Plackett-Burman design of experiments was used in the statistical screening of variables and then transformed to a full-factorial design based on the significant variables. According to the experimental findings, dilute acid hydrolysis can yield a considerable amount of soluble carbohydrates. The goodness of fit of the model was evaluated using the coefficient of determination. The optimized carbohydrate yields of the biomass were 0.76 g/g cassava peels, 0.35 g/g sugar beet pulp, and 0.36 g/g green macroalgae. Bioethanol production from optimized hydrolysis conditions using Saccharomyces cerevisiae and Scheffersomyces stipitis DSM 3651, led to a maximum ethanol yield of 0.286 g/g from cassava peels and 0.033 g/g from sugar beet pulp, while using Neurospora intermedia DSM 1265 led to a maximum ethanol yield of 0.076 g/g from green macroalgae. Hence, these biomasses are considered valuable feedstock for bioethanol production with cassava peels having the highest potential.

Green Extraction of Pectin from Sugar Beet Flakes and Its Application in Hydrogels and Cryogels.

Sugar beet flakes, a by-product of the sugar industry, were used as a source for pectin extraction that was performed using conventional citric acid extraction (CE) and two non-conventional extraction techniques-microwave-assisted extraction (MAE) and pulsed ultrasound-assisted extraction (PUAE). The influence of extraction conditions was studied for each technique based on pectin yield and galacturonic acid content, and spectroscopic, chromatographic and colorimetric methods were used for pectin characterization. Better results for pectin yield were achieved through CE (20.80%), while higher galacturonic acid content was measured in pectin extracted using PUAE (88.53 g/100 g). Pectin extracted using PUAE also presented a higher degree of methylation and acetylation. A significant increase in the molecular weight of pectin was observed for the PUAE process (7.40 × 105 g/mol) by comparison with conventional extraction (1.18 × 105 g/mol). Hydrogels and cryogels prepared with pectin from sugar beet flakes also showed differences in physicochemical parameters determined by the method of pectin extraction. Hydrogels had higher bulk density values irrespective of the pectin extraction method, and overall lower values of the textural parameters. Cryogels prepared with pectin from CE showed higher values of the textural parameters of hardness, adhesiveness, cohesiveness, gumminess and chewiness, while gels obtained with pectin from MAE and PUAE had higher thermal stability. The results of this study prove that sugar beet flakes can be considered a potential source for pectin production, and the extracted pectin is suitable for obtaining hydrogels and cryogels with physicochemical parameters comparable to the commercial citrus and apple pectin available on the market.

Trends in global sugar beet production and sugar consumption levels

Relevance. Sugar beet is one of the raw materials from which granulated sugar is produced, and it, in turn, is one of the indicators by which the food security of any country is assessed. In 2020, European countries produced 47.6% of the total global volume of sugar beet, Asian countries — 18.6%, America — 13.3%, the Russian Federation — 13.7%, African countries — 6.7%. At the same time, the share of sugar beet production in global production increased in Asian countries (from 15.9% in 2010 up to 18.6% in 2020), in the Russian Federation (from 10.1 to 13.7%), in African countries (from 4.6 to 6.7%). A decrease in sugar beet production was noted in European countries — from 55.4% in 2010 to 47.6% in 2020, in American countries — from 14 to 13.3%. In the Russian Federation, sugar production per capita generally meets not only rational consumption standards, but also all criteria for food self-sufficiency. The excess of actual consumption over rational consumption in Russia is 62.5%. The lowest sugar beet production volumes are observed in countries such as Greece, Portugal, North Macedonia, Pakistan, Azerbaijan, Turkmenistan, Kazakhstan, Moldova, Kyrgyzstan, and some others.Results. The results of the study showed that in order to increase the economic indicators of sugar beet production, Russian commodity producers need to implement a policy of intensification of agricultural production along with updating the material and technical base using modern agricultural technologies and the development of their own breeding and genetic centers.

Spatially Explicit Active Learning for Crop-Type Mapping from Satellite Image Time Series.

The availability of a sufficient number of annotated samples is one of the main challenges of the supervised methods used to classify crop types from remote sensing images. Creating these samples is time-consuming and costly. Active Learning (AL) offers a solution by streamlining sample annotation, resulting in more efficient training with less effort. Unfortunately, most of the developed AL methods overlook spatial information inherent in remote sensing images. We propose a novel spatially explicit AL that uses the semi-variogram to identify and discard redundant, spatially adjacent samples. It was evaluated using Random Forest (RF) and Sentinel-2 Satellite Image Time Series in two study areas from the Netherlands and Belgium. In the Netherlands, the spatially explicit AL selected 97 samples achieving an overall accuracy of 80%, compared to traditional AL selecting 169 samples with 82% overall accuracy. In Belgium, spatially explicit AL selected 223 samples and obtained 60% overall accuracy, while traditional AL selected 327 samples and obtained an overall accuracy of 63%. We concluded that the developed AL method helped RF achieve a good performance mostly for the classes consisting of individual crops with a relatively distinctive growth pattern such as sugar beets or cereals. Aggregated classes such as 'fruits and nuts' posed, however, a challenge.

Sugar accumulation stage in sugar beets is a key stage in response to continuous cropping soil microbial community assembly

Sugar accumulation stage in sugar beets is a key stage in response to continuous cropping soil microbial community assembly

Mixed ensiling of drought‐impaired grass with agro‐industrial by‐products and silage additives improves the nutritive value and shapes the microbial community of silages

AbstractDroughts lead to reduced biomass production and unfavourable nutrient composition in grassland. As an alleviation, yet unexploited strategy, mixed ensiling of grass with agro‐industrial by‐products may improve the ensilability and nutritive value of drought‐impaired grassland. This study investigated first whether mixed ensiling of drought‐impaired grass with either sugar beet pulp (SBP), wheat gluten feed (WGF) or brewers' grains (BG) has a beneficial impact on chemical composition, fermentation characteristics, in vitro gas production (GP) and physically effective neutral detergent fibre (peNDF) of silages. Secondly, it was tested whether the application of anaerobic fungi culture supernatant (AF), mixed ruminal fluid (RF) or lactic acid bacteria (LAB) provides further advantages. Additionally, the microbial community composition was evaluated in selected silages. All silages showed satisfying conservation characteristics with high lactic acid levels and low dry matter losses, and peNDF values typically found for conserved forages. Mixed ensiling with BG substantially increased the crude protein concentration, whereas SBP increased the total degradability and WGF enhanced both. The further addition of fresh AF resulted in the overall highest lactic acid levels, especially in SBP‐based silages, but without changes in in vitro GP. The in vitro GP was higher with RF, particularly in mixed silages, suggesting an improved degradability. The LAB‐treated silages showed lower pH compared to controls, but had no impact on in vitro GP kinetics. Concluding, mixed ensiling holds potential to produce high‐quality silages from drought‐impaired grassland. The further addition of silage additives can be useful for certain substrates, but appeared not mandatory.

Математическое обеспечение информационно-управляющей системы для хранения продукции с ограниченным сроком хранения

The work presents a solution to the problem of developing mathematical support for an information and control system for storing products with a limited shelf life using the example of storing sugar beets in field conditions and in heaps at sugar factories based on experimental experiments published in the open press data. An end-to-end ranking of methods for storing root crops was carried out, starting with a root lying separately on the field (rank 0.1 points), from simple windrows and heaps (rank 0.2 points) to specialized root storage and ventilated piles covered with special bactericidal coatings with reflective and protective properties (rank 4 points). An end-to-end ranking of mechanical damage to sugar beet roots has been implemented, starting from 1 point (the root crop is practically undamaged) to 0.1 point (fragments and tails). The studied hybrids were ranked according to sugar content. Based on the rankings, taking into ac-count storage time and temperature, mathematical models (mm) of the dependence of technological indica-tors of beet raw materials, including losses of beet mass and sucrose, on storage parameters were built for each study. Extensive computational experiments were per-formed using an interactive identification and optimization system (isio), which is based on a genetic algorithm and the Hooke Jeeves nonlinear programming method. The errors of the developed models do not exceed the errors of the experimental data used to construct them.

Comparative genomics, pangenomics, and phenomic studies of Pectobacterium betavasculorum strains isolated from sugar beet, potato, sunflower, and artichoke: insights into pathogenicity, virulence determinants, and adaptation to the host plant.

Bacteria of genus Pectobacterium, encompassing economically significant pathogens affecting various plants, includes the species P. betavasculorum, initially associated with beetroot infection. However, its host range is much broader. It causes diseases of sunflower, potato, tomato, carrots, sweet potato, radish, squash, cucumber, and chrysanthemum. To explain this phenomenon, a comprehensive pathogenomic and phenomic characterisation of P. betavasculorum species was performed. Genomes of P. betavasculorum strains isolated from potato, sunflower, and artichoke were sequenced and compared with those from sugar beet isolates. Metabolic profiling and pathogenomic analyses were conducted to assess virulence determinants and adaptation potential. Pathogenicity assays were performed on potato tubers and chicory leaves to confirm in silico predictions of disease symptoms. Phenotypic assays were also conducted to assess the strains ability to synthesise homoserine lactones and siderophores. The genome size ranged from 4.675 to 4.931 kbp, and GC % was between 51.0% and 51.2%. The pangenome of P. betavasculorum is open and comprises, on average, 4,220 gene families. Of these, 83% of genes are the core genome, and 2% of the entire pangenome are unique genes. Strains isolated from sugar beet have a smaller pangenome size and a higher number of unique genes than those from other plants. Interestingly, genomes of strains from artichoke and sunflower share 391 common CDS that are not present in the genomes of other strains from sugar beet or potato. Those strains have only one unique gene. All strains could use numerous sugars as building materials and energy sources and possessed a high repertoire of virulence determinants in the genomes. P. betavasculorum strains were able to cause disease symptoms on potato tubers and chicory leaves. They were also able to synthesise homoserine lactones and siderophores. The findings underscore the adaptability of P. betavasculorum to diverse hosts and environments. Strains adapted to plants with high sugar content in tissues have a different composition of fatty acids in membranes and a different mechanism of replenishing nitrogen in case of deficiency of this compound than strains derived from other plant species. Extensive phenomics and genomic analyses performed in this study have shown that P. betavasculorum species is an agronomically relevant pathogen.

Ecological characteristics of sugar beet plant and rhizosphere soil in response to high boron stress: A study of the remediation potential

High boron (B) stress degrades the soil environment and reduces plant productivity. Sugar beet has a high B demand and potential for remediation of B-toxic soils. However, the mechanism regarding the response of sugar beet plants and rhizosphere soil microbiome to high B stress is not clear. In the potted soil experiment, we set different soil effective B environments (0.5, 5, 10, 30, 50, and 100 mg kg−1) to study the growth status of sugar beets under different B concentrations, as well as the characteristics of soil enzyme activity and microbial community changes. The results showed that sugar beet growth was optimal at 5 mg kg−1 of B. Exceeding this concentration the tolerance index decreased. The injury threshold EC20 was reached at an available B concentration of 35.8 mg kg−1. Under the treatment of 100 mg kg−1, the B accumulation of sugar beet reached 0.22 mg plant−1, and the tolerance index was still higher than 60%, which had not yet reached the lethal concentration of sugar beet. The abundance of Acidobacteriota, Chloroflexi and Patescibacteria increased, which was beneficial to the resistance of sugar beet to high B stress. In summary, under high B stress sugar beet had strong tolerance, enhanced capacity for B uptake and enrichment, and changes in soil microbial community structure. This study provides a theoretical basis for clarifying the mechanism of sugar beet resistance to high B stress and soil remediation.

Hot-air drying vs. lyophilization of sugar beet flakes for efficient pectin recovery and influence of extraction conditions on pectin physicochemical properties

This study assessed the influence of drying pretreatment and extraction conditions (type of acid and particle size of plant material) on the yield and physicochemical properties of pectin from sugar beet flakes resulted as by-product of sugar beet processing in the sugar industry. The results indicated that the drying conditions (hot-air drying and lyophilization) affected the extraction yield, the chemical composition of pectin, its color, degree of methylation and acetylation, molecular weight, and its rheological and emulsifying properties. The best results for pectin yield (16.20%), galacturonic acid content (91.19 g/100 g), degree of methylation and acetylation (66.93 and 23.87%), and molecular weight (3.89 × 105 g/mol) were obtained when sugar beet flakes were pretreated by hot-air drying, and the extraction was made with citric acid using plant material with particle sizes of 125–200 μm. This pectin also had high emulsion activity (51.42%) and emulsion stability (88.03%). The FT-IR spectra were similar, while pectin thermal behavior was affected by the drying pretreatment and extraction conditions. The results of this study showed that from this by-product of the sugar industry it can be extracted high quality pectin with rheological and emulsifying properties that are superior to commercial citrus and apple pectin.

Crop Type Classification using Sentinel 2A-Derived Normalized Difference Red Edge Index (NDRE) and Machine Learning Approach

Abstract Satellite remote sensing (RS) enables the extraction of vital information on land cover and crop type. Land cover and crop type classification using RS data and machine learning (ML) techniques have garnered considerable attention in the scientific community. This study aimed to enhance the field of remote sensing research using high-resolution satellite imagery and the ML approach. To reach this goal, machine learning techniques were used to demonstrate whether they could accurately classify different types of crops in farming areas using the Normalized Difference Red Edge Index (NDRE) from Sentinel 2A. Five ML classifiers, namely Support Vector Machines (SVM), Random Forest (RF), Decision Tree (DT), K-Nearest Neighbors (KNN), and Multi-Layer Perceptron (MLP) were implemented using Python programming on Google Colaboratory. The target crop classes included cereals, fallow, forage, fruits, grassland-pasture, legumes, maize, sugar beet, onion-garlic, sunflower, and watermelon-melon. The classification models exhibited strong performance, as evidenced by their robust overall accuracy (OA). The RF model outperformed, with an OA rate of 95% and a Kappa score of 92%. It was followed by DT, KNN, SVM, and MLP with an OA of 88%, 87%, 85%, and 82%, respectively. This study confirmed the potential enhancement of the application of high spatial resolution satellite RS data and ML for crop type classification, especially in regions that have received less attention in previous studies.

Seed bio-/chemo-priming affects the reaction of sugar beet plants to Beet curly top virus-Svr

Seed bio-/chemo-priming affects the reaction of sugar beet plants to Beet curly top virus-Svr

Development of an Integrated Bioprocess System for Bioethanol and Arabitol Production from Sugar Beet Cossettes.

An innovative integrated bioprocess system for bioethanol production from raw sugar beet cossettes (SBC) and arabitol from remaining exhausted sugar beet cossettes (ESBC) was studied. This integrated three-stage bioprocess system is an example of the biorefinery concept to maximise the use of raw SBC for the production of high value-added products such as sugar alcohols and bioethanol. The first stage of the integrated bioprocess system was simultaneous sugar extraction from SBC and its alcoholic fermentation to produce bioethanol in an integrated bioreactor system (vertical column bioreactor and stirred tank bioreactor) containing a high-density suspension of yeast Saccharomyces cerevisiae (30 g/L). The second stage was the pretreatment of ESBC with dilute sulfuric acid to release fermentable sugars. The resulting liquid hydrolysate of ESBC was used in the third stage as a nutrient medium for arabitol production by non-Saccharomyces yeasts (Spathaspora passalidarum CBS 10155 and Spathaspora arborariae CBS 11463). The obtained results show that the efficiency of bioethanol production increased with increasing temperature and prolonged residence time in the integrated bioreactor system. The maximum bioethanol production efficiency (87.22 %) was observed at a time of 60 min and a temperature of 36 °C. Further increase in residence time (above 60 min) did not result in the significant increase of bioethanol production efficiency. Weak acid hydrolysis was used for ESBC pretreatment and the highest sugar yield was reached at 200 °C and residence time of 1 min. The inhibitors of the weak acid pretreatment were produced below bioprocess inhibition threshold. The use of the obtained liqiud phase of ESBC hydrolysate for the production of arabitol in the stirred tank bioreactor under constant aeration clearly showed that S. passalidarum CBS 10155 with 8.48 g/L of arabitol (YP/S=0.603 g/g and bioprocess productivity of 0.176 g/(L.h)) is a better arabitol producer than Spathaspora arborariae CBS 10155. An innovative integrated bioprocess system for the production of bioethanol and arabitol was developed based on the biorefinery concept. This three-stage bioprocess system shows great potential for maximum use of SBC as a feedstock for bioethanol and arabitol production and it could be an example of a sustainable 'zero waste' production system.

Effect on calf growth of accounting for early in vitro degradation kinetics when composing a calf starter ration

Degradation kinetics of concentrates were investigated in vitro and fed to calves to determine if weight gains reflected in vitro results. Five concentrate ingredients (steam dried sugar beet pulp, drum dried sugar beet pulp, toasted faba beans, untreated faba beans and soybean hulls) were fermented using the in vitro gas production technique in two 48 hour fermentations and degradation parameters were established. Two pairs of calf starter rations were formulated based on the in vitro degradation profiles of the individual concentrates and pelleted. The rations were balanced using NorFor – the Nordic feed evaluation system- to provide a similar net energy (MJ/day) but with differing in vitro degradation kinetics during the first 16 h of fermentation. Each pair consisted of rations made with concentrate ingredients that had an expected in vitro rapid (“Fast”) degradation and an expected in vitro slower (“Slow”) degradation relative to each other during the first 16 h of fermentation. The first pair (Fast_1 and Slow_1) consisted mainly of a single fast or slow in vitro degraded concentrate ingredient, either steam dried sugar beet pulp (48.5 % of dry matter) or drum dried sugar beet pulp (49.5 %), respectively. The second pair (Fast_2 and Slow_2) included two expected fast or slow in vitro degraded ingredients. The extra “Fast” concentrate ingredient, in addition to steam dried sugar beet pulp, was untreated faba beans, which brought the total fast concentrate ingredients in the Fast_2 ration to 64 % of DM. The second “Slow” concentrate ingredient was toasted faba beans, in addition to soybean hulls, which replaced the drum dried sugar beet pulp. The total “Slow” ingredients in the Slow_2 ration was 65.8 % of DM. The first pair of concentrate rations were each fed to 18 calves on a commercial dairy farm, while the second pair was fed to 59 calves each on a beef fattening station. The calves were fed for 8 weeks, and each calf was weighed weekly. The mean total weight gain of each calf after the trial was 68.5 kg and 68.6 for Fast_1 and Slow_1, respectively and 64.9 kg and 63.8 kg for Fast_2 and Slow_2, respectively. There was a tendency for Slow_1 to lead to increased growth compared to Fast_1 (P=0.052), when accounting for the initial weight of the calves, but there were no differences between Fast_2 and Slow_2. There was no significant effect on feed efficiency. The large differences in fermentation kinetics seen in the concentrate ingredients in vitro were not seen in the concentrate rations or the weight gain response of the growing calves.

Assessing the impact of seasonality on bioenergy production from energy crops in Germany, considering just‐in‐time philosophy

AbstractThe availability of biomass is strongly influenced by seasonality, which can affect the production of biofuels, biogas, and bio‐based products in the downstream bioenergy supply chain. Rapeseed, maize silage, sugar beet, wheat, and grass from grassland are the most popular energy crops; they play a significant role in the German bioenergy strategy and are being discussed extensively in the current gas shortage context. Most models in the literature assume yearly temporal resolution for these energy crops, which can negatively impact the accuracy of results. This problem is increasingly relevant under weather conditions that are varying increasingly due to climate change; in this study we therefore employ the extended bioenergy optimization model (BENOPTex) to explore the impact of seasonality on the optimal deployment of biomass from energy crops in bioenergy production in the German heat, power, and transport sectors, which typically show high dependency on fossil fuels. First, we increased the model's temporal resolution using available datasets and documents. Next, the varying availability factors were embedded in the optimization model, considering the no‐storage policy for energy crops in accordance with the just‐in‐time philosophy. Finally, the outcomes of the BENOPTex with annual resolution were contrasted with the results including the effects of seasonality, while considering various objective functions. We demonstrated a shift toward the consumption of woody biomass until 2045 due to its longer shelf life and improved storability. The energy demand stemming from summer leisure travel was also anticipated to exceed the bioenergy system's capacity. The insights provided here might be interesting for policymakers who design roadmaps for bioenergy development with a more resilient energy supply.