• Energy Research

The estimation of biophysical and biochemical parameters using Sentinel-2 satellite imagery provides crucial information to support agronomic management and logistics for the processing industry, yet this approach has been poorly explored for vegetable crops, such as spinach (Spinacia oleracea L.). For this reason, Sentinel-2 satellite images were used to estimate biophysical and biochemical parameters of open field spinach crops (Above Ground Biomass (AGB), Canopy Nitrogen Content (CNC), Leaf Area Index (LAI), Canopy Chlorophyll Content (CCC), Leaf Dry Matter Content (LDMC), Leaf Nitrogen Content (LNC), Leaf Nitrate Content (LNO3−C) and Leaf Chlorophyll Content (LCC)). Spinach samples were collected in northern Italy in two different growing seasons (2020 – 2021) to measure biophysical and biochemical parameters which were linearly regressed via linear regression k-fold to five vegetation indices retrieved from Sentinel-2 images (MCARI, NDRE, NDVI, NDWI and SR). The AGB estimation models were also validated at field scale using historical data, totally independent from those used for the model calibration, collected by the processing industry between 2018 and 2021. Overall, canopy-level parameters (AGB, LAI, CNC, CCC) were estimated more accurately than leaf-level parameters (LDMC, LNC, LNO3−C, LCC). The highest accuracy was observed for the estimation of the canopy-scale parameter AGB (nRMSE = 9.48 %, R2 = 0.87) using MCARI, while the lowest accuracy was observed for the estimation of the leaf-scale parameter LCC (nRMSE = 29.24 %, R2 = 0.01) using NDWI. At field level, the validation of the AGB estimation models showed the highest performance using SR (nRMSE = 19.69 %, R2 = 0.21). This work demonstrates that using Sentinel-2 satellite images, it is feasible to estimate biophysical and biochemical parameters useful for monitoring the health of spinach crops for both agronomic management and the industrial supply chain.

The optimal combination of yield and quality of hemp fibres from field grown crops is around flowering. Therefore prediction of flowering time would support in planning production and optimization of the cultivar choice for different agro-ecological zones. In the current paper the validation of a recently published model (Amaducci et al., 2008a) is carried out for four varieties across a wide range of sites and thus of air temperature–photoperiod combinations. The model was evaluated by comparing its output to field observations of the duration between emergence and 50% flowering. The model output and observed times from emergence to 50% of flowering generally corresponded well, but some discrepancies were apparent. The biggest discrepancies between estimates and actual data were observed at extreme latitudes. The level of accuracy of the model predictions is satisfactory for strategic decision regarding sowing and harvesting time and cultivar choice, but tactical decisions (e.g. time of harvest based on flowering time) cannot be accurately supported

We hypothesize that the current heated scientific debate on bioenergy sustainability is fuelled by flaws in the interpretation phase of bioenergy LCA studies rather than by the lack of studies or shared methodologies. The interpretation phase is the key step in LCA studies, which guarantees their quality and consistency and gives meaning to the work carried out by delivering results that are consistent with the defined goal and scope, which reach conclusions, and explain limitations. To test our hypothesis, we selected the 100 most cited articles found in Scopus utilizing a query to include most of the relevant works on LCA of bioenergy. The rationale underpinning the choice of the most cited articles is that these are presumably the most influential. A further screening identified off-topic articles, reviews, and methodological papers, which were discarded. We have also checked whether the articles analysed referred to the ISO standards. The study is organized as a reasoned and parametrized review in which we assess the methodological approach of the studies, rather than the results obtained. We find that overlooking some of the fundamental steps in the interpretation phase in bioenergy LCA is a rather common practice. Although most of the studies referred to the ISO standards, the identification of issues, their framing with sensitivity analyses, and the identification and reporting of limitations, which are all needed to comply with ISO14044 standards, are often neglected by practitioners. The most problematic part of the interpretation phase is the consistency check. In most cases, the assessment framework built is not apt at answering the question set in the goal. Limitations are properly identified and reported only in few studies. We conclude that in many studies either the conclusions and recommendations drawn are not robust because the inventory and the impact assessment phases are not consistent with the goal of the study, or the conclusions and recommendations go well beyond what the limitations of the study would allow. In our opinion, these flaws in the interpretation phase of influential LCA studies are among the responsible factors that continue to fuel the debate around the sustainability of bioenergy. We report a set of recommendations both for LCA practitioners and for users to guide the LCA practitioners in properly organizing and reporting their work, and to facilitate the readers in understanding and evaluating the significance and applicability of the results presented.

Abstract Bioenergy buffers are linear landscape elements cultivated with perennial herbaceous or woody biomass crops placed along arable field margins and watercourses. This systematic review evaluates the potential impact of bioenergy buffers on multiple ecosystem services (ES) provision while describing key factors along the biomass supply chain. An Impact Assessment (IA) methodology was adopted to capture the direction and the level of confidence of impact on multiple ES including regulating (climate, water and biodiversity), supporting (soil health) and provisioning services (biomass and energy yield). The IA revealed that the implementation of bioenergy buffers on previous croplands rather than on grasslands sustains long-term provision of multiple ES such as climate, water quality and biodiversity regulation and soil health. Herbaceous buffers were found to be more effective than woody buffers in the provision of multiple ES. Knowledge gaps relative to climate and water quality regulation services were identified for the establishment phase of bioenergy buffers (0-3y). Regarding biomass logistics, the limited operating space for farm machinery was the main shortcoming when comparing bioenergy buffers to large-scale bioenergy plantations. The intra- and inter-farm spatial fragmentation of biomass supply areas may increase environmental costs related to biomass collection and transport operations, but this has not yet been fully tested. Establishing a network of bioenergy buffers increases landscape connectivity and the overall area of ES provision in the agricultural landscape. Payments for ES obtained from bioenergy buffers can ultimately improve the economics of sustainable bioenergy and help achieving environmental goals of EU policies on water, soil and biodiversity protection.

Decomposition models of solar irradiance estimate the magnitude of diffuse horizontal irradiance from global horizontal irradiance. These two radiation components are well-known to be essential for the prediction of solar photovoltaic systems performance. In open-field agrivoltaic systems, that is the dual use of land for both agricultural activities and solar power conversion, cultivated crops receive an unequal amount of direct, diffuse and reflected photosynthetically active radiation (PAR) depending on the area they are growing due to the non-homogenously shadings caused by the solar panels installed (above the crops or vertically mounted). It is known that PAR is more efficient for canopy photosynthesis under conditions of diffuse PAR than direct PAR per unit of total PAR. For this reason, it is fundamental to estimate the diffuse PAR component in agrivoltaic systems studies to properly predict the crop yield. Since PAR is the part of electromagnetic radiation in the waveband from 400 to 700 nm that can be used for photosynthesis by the crops, several stand-alone decomposition models of solar irradiance are selected in this study to partition PAR into direct and diffuse. These models are applied and validated in three locations in Sweden: Lanna, Hyltemossa and Norunda, using the coefficients stated on the original publications of the models and locally fitted coefficients. Results showed weaker performances in all stand-alone models for non-locally fitted coefficients (nRMSE ranging from 29% to 95%). However, performances improve with re-parameterization, reaching highest nRMSE of 37.94% in Lanna. YANG2 decomposition model is the best-performing one, reaching lowest nRMSE of 24.31% in Norunda applying re-estimated coefficients. Country level sets of coefficients for the best-performing models, YANG2 and STARKE, are given after parameterization using joined data of the three locations in Sweden. These Sweden-fitted models are tested and showing nRMSE of 25.56% (YANG2) and 28.36% (STARKE). These results can be used to perform estimations of PAR diffuse component in Sweden where measurements are not available, and the overall methodology can be similarly applied to other countries.

Abstract A major constraint to the use of biomass sorghum varieties (Sorghum bicolor (L.) Moench) to generate electricity by direct combustion is the high biomass moisture content at harvest that, under unfavourable weather conditions during field drying limits the possibility to achieve a suitable moisture content for baling. In this work, the CropSyst model was calibrated and validated with data collected in experimental trials conducted in the Po Valley (northern Italy). It was then used to simulate biomass production of three sorghum varieties of contrasting earliness (early, medium-late, and late). In order to simulate the dynamics of biomass moisture content during field drying, a specific model, “sorghum haying model”, was developed and validated. The two models combined were used to simulate, for three sorghum varieties of contrasting earliness (early, medium-late and late), biomass production and the probability to achieve during field drying a biomass moisture content suitable for baling. In a long term simulation (140 years), the late sorghum variety achieved the highest dry biomass production (16.5 Mg ha−1) followed by the medium-late (15.4 Mg ha−1) and early (15.1 Mg ha−1) variety. The early variety had the highest probability (0.66) of being baled at a moisture content ≤ 18%, followed by the medium-late (0.53) and late (0.37) varieties. The early variety, also having the shortest average field drying (9.2 days), was considered the most suitable for the selected environmental conditions.

Abstract The purpose of this work was to assess biomass and grain yields, path modelling of yield components, and perenniality in 97 Sorghum bicolor x S. halepense (SB x SH) lines, and compare their biomass production to a series of 38 historic (1987–2015) biomass SB trials. Perenniality was evaluated as rhizome overwintering, while other traits were scored using standard procedures. Contrary to SB, several SB x SH lines developed rhizomes and overwintered, depending mostly upon increased dosage of SH genome in SB background. A few backcross-derived SB x SH lines overwintered, indicating that perenniality can be introgressed in sorghum using backcrossing approach. SB x SH lines were competitive in terms of grain and aboveground dry biomass yields compared to SB. SB x SH selections outperformed or were comparable to the best commercial biomass SB hybrid checks, and ranked among the best selections from the historic trials. Grain yield in SB x SH lines depended mainly on number of culms, whereas biomass yields depended mainly on plant height, dry mass and fiber mass fractions of dry material, and number of culms. We identified superior dual purpose SB x SH genotypes producing 5–11 and 38–45 t ha−1 of grain and aboveground biomass, respectively, most of which displayed satisfactory overwintering rates (56–100%) and high levels of fiber (61–69%) mass fraction. These lines represent high energy sorghums suitable for biofuel and food production. The best SB x SH crosses for developing perennial biomass and grain sorghums were represented by perennial/perennial, annual/perennial/perennial, and annual/perennial combinations.

Sorghum (Sorghum bicolor L.) is a very interesting biofuel feedstock crop. With C4 photosynthesis and drought tolerance, it is suitable for cultivation in water limited environments and could be a key crop in a warmer and unpredictable global climate. Furthermore, sorghum can be used for ethanol production from both 1st and 2nd generation technologies (using sweet/grain genotypes or biomass genotypes, respectively). The potential use of commercial sorghum genotypes for the production of 2nd generation ethanol was investigated in a two year project in Northern Italy. Fields trials were carried out for two years in two locations on a selection of genotypes to optimize agronomical technique, identifying in particular the effect of plant density, irrigation, fertilization, time of harvesting on crop yield. Biomass compositions were analysed for all genotypes while ethanol yield was estimated on three genotypes at harvest and after conservation. Pretreatment, hydrolysis and fermentation were carried out with the innovative technology developed by Chemtex. Biomass yield was on average 22.6 Mg ha-1, with large differences among genotypes, environments and cultivation techniques so that extreme yield of 10.6 and 38.4 Mg ha-1 were measured. Percentage of fermentable sugars on dry matter in the genotypes under trial varied from 47% to 60%, and glucans were on average 63% of the fermentable sugars in both years. Average Klason lignin and acetyl content were, respectively, 12.8% and 1.7%. Biomass composition varied significantly among genotypes. The test carried out on biomass preserved by on field drying or silage showed that the latter method results in high ethanol yield reduction and is therefore not a suitable option for sorghum conservation. In general biomass sorghum can be considered an interesting crop for 2nd generation ethanol production. Keywords: Sorghum bicolor, 2nd generation ethanol, cultivation, processing, conservation.