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Abstract The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N−) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.

Abstract Longer term monitoring of soil water content at a catchment scale is a key to understanding its dynamics, which can assist stakeholders in decision making processes, such as land use change or irrigation programs. Soil water monitoring in agriculturally dominated catchments can help in developing soil water retention measurements, for assessment of land use change, or adaptation of specific land management systems to climate change. The present study was carried out in the Pannonian region (Upper-Balaton, Hungary) on Cambisols and Calcisols between 2015 and 2021. Soil water content (SWC) dynamics were investigated under different land use types (vineyard, grassland, and forest) at three depths (15, 40, and 70 cm). The meteorological data show a continuous decrease in cumulative precipitation over time during the study with an average of 26% decrease observed between 2016 and 2020, while average air temperatures were similar for all the studied years. Corresponding to the lower precipitation amounts, a clear decrease in the average SWC was observed at all the land use sites, with 13.4%, 37.7%, and 29.3% lower average SWC for the grassland, forest, and vineyard sites, respectively, from 2016 to 2020 (measured at the 15 cm depth of the soil). Significant differences in SWC were observed between the annual and seasonal numbers within a given land use (p < 0.05). The lowest average SWC was observed at the grassland (11.7%) and the highest at the vineyard (28.3%). The data showed an increasing average soil temperature, with an average 6.3% higher value in 2020 compared to 2016. The grassland showed the highest (11.3 °C) and the forest soil the lowest (9.7 °C) average soil temperatures during the monitoring period. The grassland had the highest number of days with the SWC below the wilting point, while the forest had the highest number of days with the SWC optimal for the plants.

AbstractThe bioenergy crops such as energycane, miscanthus, and sorghum are being genetically modified using state of the art synthetic biotechnology techniques to accumulate energy‐rich molecules such as triacylglycerides (TAGs) in their vegetative cells to enhance their utility for biofuel production. During the initial genetic developmental phase, many hundreds of transgenic phenotypes are produced. The efficiency of the production pipeline requires early and minimally destructive determination of oil content in individuals. Current screening methods require time‐intensive sample preparation and extraction with chemical solvents for each plant tissue. A rapid screen will also be needed for developing industrial extraction as these crops become available. In the present study, we have devised a proton relaxation nuclear magnetic resonance (1H‐NMR) method for single‐step, non‐invasive, and chemical‐free characterization of in‐situ lipids in untreated and pretreated lignocellulosic biomass. The systematic evaluation of NMR relaxation time distribution provided insight into the proton environment associated with the lipids in the biomass. It resolved two distinct lipid‐associated subpopulations of proton nuclei that characterize total in‐situ lipids into bound and free oil based on their “molecular tumbling” rate. The T1T2 correlation spectra also facilitated the resolution of the influence of various pretreatment procedures on the chemical composition of molecular and local 1H population in each sample. Furthermore, we show that hydrothermally pretreated biomass is suitable for direct NMR analysis unlike dilute acid and alkaline pretreated biomass which needs an additional step for neutralization.

Results-based financing (RBF) programmes in the clean cooking sector have gained increasing donor interest over the last decade. Although the risks and advantages of RBF have been discussed quite extensively for other sectors, especially health services, there is limited research-documented experience of its application to clean cooking. Due to the sheer scale of the important transition from ‘dirty’ to clean cooking for the 4 billion people who lack access, especially in the Global South, efficient and performance-proven solutions are urgently required. This paper, undertaken as part of the work of the UKAid-funded Modern Energy Cooking Services (MECS) programme, aims to close an important research gap by reviewing evidence-based support mechanisms and documenting essential experiences from previous and ongoing RBF programmes in the clean cooking and other sectors. On this basis, the paper derives key strategic implications and learning lessons for the global scaling of RBF programmes and finds that qualitative key performance indicators such as consumer acceptance as well as longer-term monitoring are critical long-term success factors for RBF to ensure the continued uptake and use of clean cooking solutions (CCS), however securing the inclusion of these indicators within programmes remains challenging. Finally, by discussing the opportunities for the evolution of RBF into broader impact funding programmes and the integration of energy access and clean cooking strategies through multi-sector approaches, the paper illustrates potential steps to enhance the impact of RBF in this sector in the future.

This work has been developed under the AGROinLOG Project, “Demonstration of innovative integrated biomass logistics centres for the Agro-industry sector in Europe”. An Integrated Biomass Logistics Center (IBLC), is based on the introduction of new production chains into existing agro-industries by using new biomass feedstock. The AGROinLOG Project has dedicated great attention to investigate the potential of cereal chaff as a valuable resource.Chaff is the fine fraction of the thrashing residues, not usually collected. Chaff is made up of glumes, seed husks, rachis and the tinner part of the cereal stems, whole and cracked kernels, as well as weed seeds.Currently there are several mechanical solutions available on the market for chaff recovery, and others are still at prototype stage, but theyare not so common and very often unknown to the farmers.So far, the literature reportsfew cases of chaff collection with the specific purpose of weed seeds removal, but it still lacks specificexperiments on these machinesintentionally used for biomass collection.For this reason, during the Project AGROinLOG a series of large field tests were performed using an independent scientific approach with different kind of chaff harvesting technologiesin France, Sweden and Italy from 2017 to 2019.The present study collects the results of these activities with the aim to fill that gap and provide deeper understanding in the possibility to enhance the current cereal harvesting method, in order to improve the quantity of biomass collected by including the chaff. Proceedings of the 29th European Biomass Conference and Exhibition, 26-29 April 2021, Online, pp. 62-68

AbstractAimAgriculture is one of the greatest pressures on biodiversity. Regional studies have shown that the presence of natural habitat and landscape heterogeneity are beneficial for biodiversity in agriculture, but it remains unclear whether their importance varies geographically. Here, we use local biodiversity data to determine which local and landscape variables are most associated with biodiversity patterns and whether their association varies between tropical and non‐tropical regions.LocationGlobal terrestrial area in forest biomes.Major taxa studiedMore than 21,000 species of vertebrates, invertebrates, plants and other taxa.MethodsWe used generalized linear mixed‐effects models to analyse the relationships between either community total abundance or species richness (derived from the PREDICTS database) and a number of site‐level (predominant land use and land‐use intensity) and landscape‐level variables (distance to forest, the percentage of natural habitat in the surrounding landscape, landscape homogeneity, the number of land‐cover types in the landscape, and total fertilizer application). We compared the associations of these variables with biodiversity in tropical and non‐tropical regions.ResultsIn most cases, changes in biodiversity associated with landscape‐level variables were greater than those associated with local land use and land‐use intensity. Increased natural habitat availability was associated with the most consistent increases in biodiversity. Landscape homogeneity was also important but showed different directions of biodiversity change between regions. Associations with fertilizer application or the number of land‐cover types were generally weaker, although still of greater magnitude than for the local land‐use measures.Main conclusionsOur results highlight similarities and differences in the association of local‐ and landscape‐scale variables with local biodiversity in tropical and non‐tropical regions. Landscape natural habitat availability had a consistent positive association with biodiversity, highlighting the key role of landscape management in the maintenance of biodiversity in croplands. Landscape‐scale variables were almost always associated with greater changes in biodiversity than the local‐scale measures.

Cassava utilisation in Malawi is negatively affected by rapid deterioration of fresh roots, primarily caused by postharvest physiological deterioration (PPD). A study was conducted to assess farmers’ knowledge and approaches used to minimize losses from PPD. Multi-stage sampling was used to identify districts, Extension Planning Areas (EPA’s) and farmers. Data were collected from 519 farmers using a structured questionnaire. Results revealed that PPD (74.0%) was the major post-harvest constraint followed by pests and diseases (62.1%). Farmers had varying knowledge levels on signs and causes of PPD. They were knowledgeable on PPD signs with 91.5% ably identifying PPD through change of pulp colour. The farmers also had moderate knowledge on causes of PPD, citing high temperature (57.6%) and over-staying of roots (56.2%) as main causes of PPD. Key methods for preventing PPD are: storage (43.0%) and piece-meal harvesting (40.4%). Only 2.6% of the farmers exploited varietal difference in dealing with PPD as some varieties (Sauti, Mpuma, Ching’amba, and Kalasa) take three to five days before showing PPD signs. Farmers’ knowledge levels and PPD preventive methods could be strengthened through: provision of training on post-harvest handling, improvement in storage and processing technologies; and application of advanced breeding techniques to exploit genetic variation in cassava germplasm.