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Miscanthus holds a promise as a biocrop due to its high yield, perenniality and ability to grow on infertile soils. However, the current commercial biomass production of Miscanthus is mostly limited to a single sterile triploid clone of M. × giganteus. Nevertheless, parental species of M. × giganteus, Miscanthus sacchariflorus and Miscanthus sinensis contain vast genetic diversity for crop improvement. With M. sacchariflorus having a natural geographic distribution in cold‐temperate northeast China and eastern Russia, we hypothesised that it has substantial variation in physiological response to chilling. Using a semi‐high‐throughput method, we phenotyped 209 M. sacchariflorus genotypes belonging to six genetic groups for non‐photochemical quenching (NPQ) and photosystem II efficiency (ΦPSII) kinetics under warm and chilling treatments in three growing seasons. In response to the chilling treatment, all genetic groups exhibited an increase in NPQ induction rate indicating faster activation of NPQ in light. Notably, under chilling, the Korea/NE China/Russia 2x and N China 2x groups stood out for the highest NPQ rate in light and the highest steady‐state NPQ in light. This NPQ phenotype may contribute adaptation to chilling during bright, cold mornings of spring and early autumn in temperate climates, when faster NPQ would better protect from oxidative stress. Such enhanced adaptation could expand the growing season and thus productivity at a given location or expand the range of economically viable growing locations to higher latitudes and altitudes. A genome‐wide association study identified 126 unique SNPs associated with NPQ and ΦPSII traits. Among the identified candidate genes were enzymes involved in the ascorbate recycle and shikimate pathway, gamma‐aminobutyric acid and cation efflux transporters. Identifying natural variation and genes involved in NPQ and ΦPSII kinetics considerably enlarges the toolbox for breeding and/or engineering Miscanthus with optimised photosynthesis under warm and chilling conditions for sustainable feedstock production for bioenergy. Chilling affects the productivity and geographical distribution of most crops. Using a semi‐high‐throughput approach to investigate photosynthesis‐related traits, we characterised variation existing in the bioenergy crop Miscanthus under chilling and warm conditions and identified potential genes associated with it. Under chilling, two genetic groups from the northern edge of Miscanthus distribution stood out for faster activation of photoprotection. This trait may contribute adaptation to chilling in temperate climates, when faster photoprotection would better defend from oxidative stress. Enhanced chilling adaptation could expand the growing season and thus productivity or enlarge the range of growing locations. [ABSTRACT FROM AUTHOR]

Practical strategies for bioenergy planning in the face of climate change should rely on ready‐to‐use yield projections. Perennial grasses grown in marginal lands (MLs) provide abundant feedstocks to be converted into different energy vectors. The aim of this study was to provide a model‐based assessment of how much energy, in the form of biomethane and bioethanol, can be achieved by Miscanthus and giant reed across Italy. Marginal lands were here conceived as low profitable non‐irrigated areas, without mechanization and/or nature conservation constraints. Marginal lands eligible for simulations were selected crossing environmental factors and ecological requirements of the two crops. The biophysical model Arungro was calibrated considering rainfed/full‐irrigated systems using multiple‐site and multiple‐year datasets. The model was connected to a georeferenced database, with information on (i) current/future climate, (ii) agronomic practices, (iii) soil physics/hydrology, (iv) MLs, and (v) crop suitability to environment and simulations were performed at 500 × 500 m spatial resolution across all Italian regions. Under baseline conditions (i.e., 1981–2010), the total area of MLs available for energy crops (i.e., 49,100 km2) allowed to obtain 23,500 (giant reed) and 23,700 (Miscanthus) Giga‐m3 CH4‐STP of biomethane and 18,600 (giant reed) and 24,400 (Miscanthus) Giga‐liters of bioethanol. While the amount of energy carriers is expected to increase, on average, of +4.6% in 2055 and + 0.4% (mean of +9.2%—South, −2.4%—Center, −5.4%—North Italy) in 2085 for Miscanthus, giant reed‐based productions are projected to be more stable across the country and time frames (+6.7% in 2055; +2.8% in 2085). This study contributed to define a modular and detailed procedure aimed at quantifying attainable energy yields from bioenergy grasses in MLs. The consideration of fine‐resolution multiple‐scale heterogeneity allowed for an in‐depth investigation of biomass productivity, attainable energy yields, and related stability under current/climate change scenarios, highlighting critical spots and opportunities within the country. [ABSTRACT FROM AUTHOR]

Agricultural lands hold significant potential for CO2 sequestration, particularly when utilizing biomass crops and agricultural residues. Among these, Miscanthus × giganteus (mxg) stands out due to its high productivity and carbon sequestration capabilities. Recognizing the importance of such biomass crops, the Intergovernmental Panel on Climate Change (IPCC) has identified Bioenergy with Carbon Capture and Storage (BECCS) as a crucial strategy for achieving net‐zero CO2 emissions by 2050. This study examines the carbon uptake potential of mxg during its establishment year at the Sustainable Advanced Bioeconomy Research (SABR) farm in Iowa, USA, where mxg was planted at a density exceeding previous studies. Using eddy covariance (EC) measurements, we quantified the net ecosystem carbon exchange (NEE), and derived gross primary productivity (GPP), and ecosystem respiration (Reco). Our findings reveal that SABR's mxg exhibited a significant carbon uptake of −621 g C m−2, a threefold increase compared to a similar EC site in the "corn‐belt" (University of Illinois Energy Research Farm; UIEF), which was established with lower planting density and pre‐commercial planting equipment. Favorable growing conditions and advanced planting technologies at SABR likely contributed to this high carbon uptake. Comparisons with other global EC studies indicated a strong correlation between higher planting densities and greater carbon uptake. These results suggest that increasing mxg planting density can enhance carbon uptake, but further studies are necessary to evaluate the impacts under varying environmental conditions and management practices. Additionally, economic analyses are essential to determine the viability of higher planting densities. Our study underscores the potential of optimized mxg management practices to contribute significantly to CO2 uptake and supports the development of BECCS as a viable climate change mitigation strategy. [ABSTRACT FROM AUTHOR]

The publication presents data on the removal of heavy metals by energy crops Miscanthus giganteus L. and Phalaris arundinacea L. when grown on technologically polluted soils. The yield of Miscanthus giganteus averaged 16.96 t/ha over the two years of research, and that of Falaris arundinacea – 4.38 t/ha, respectively. The nature of heavy metal accumulation by energy plants depended on the type of crop and its productivity during the years of cultivation. The concentration of all heavy metals in the phytomass of energy crops did not exceed the threshold limit value (TLV), except for zinc in miscanthus giganteus plants (by 9–11 mg/kg). Compared to the years of the study, in the second year of cultivation, the coefficient of heavy metal absorption by plants increased significantly compared to the first year due to an increase in the vegetative mass of plants. On average, in 2021–2023, the energy crops Phalaris arundinacea and Miscanthus x giganteus removed a significant amount of heavy metals from 1 ha of soil. It has been proven that energy crops such as Phalaris arundinacea and Miscanthus x giganteus contribute to the purification of technologically contaminated soils from heavy metals, and their products can be used further as biofuels and for other purposes, as the content of toxicants in their phytomass does not exceed the TLV. [ABSTRACT FROM AUTHOR]

Energy crops make modest but not negligible demands on soil nutrients. In grey forest soils in the Western Forest-Steppe of Ukraine and compared to rotational grain, legumes and oilseeds, 20-years cultivation of miscanthus brought about a decrease of 2.8 times of boron and 3.6 times of magnesium in the top 20 cm soil layer but an increase of 3.4 times in cobalt, 1.9 times in iron and 3 times in exchangeable calcium. Under Virginia mallow (Sida hermaphrodita L.), a reduction of boron by 1.4 times and 1.15 times of iron was found compared to soil under arable crops. The least difference between macro- and microelements was found under cup plant (Silphium perfoliatum L.). [ABSTRACT FROM AUTHOR]

Aboveground biomass (AGB) is a key indicator of crop nutrition and growth status. Accurately and timely obtaining biomass information is essential for crop yield prediction in precision management systems. Remote sensing methods play a key role in monitoring crop biomass. However, the saturation effect makes it challenging for spectral indices to accurately reflect crop changes at higher biomass levels. It is well established that rapeseed biomass during different growth stages is closely related to phenotypic traits. This study aims to explore the potential of using optical and phenotypic metrics to estimate rapeseed AGB. Vegetation indices (VI), texture features (TF), and structural features (SF) were extracted from UAV hyperspectral and ultra-high-resolution RGB images to assess their correlation with rapeseed biomass at different growth stages. Deep neural network (DNN), random forest (RF), and support vector regression (SVR) were employed to estimate rapeseed AGB. We compared the accuracy of various feature combinations and evaluated model performance at different growth stages. The results indicated strong correlations between rapeseed AGB at the three growth stages and the corresponding indices. The estimation model incorporating VI, TF, and SF showed higher accuracy in estimating rapeseed AGB compared to models using individual feature sets. Furthermore, the DNN model (R2 = 0.878, RMSE = 447.02 kg/ha) with the combined features outperformed both the RF (R2 = 0.812, RMSE = 530.15 kg/ha) and SVR (R2 = 0.781, RMSE = 563.24 kg/ha) models. Among the growth stages, the bolting stage yielded slightly higher estimation accuracy than the seedling and early blossoming stages. The optimal model combined DNN with VI, TF, and SF features. These findings demonstrate that integrating hyperspectral and RGB data with advanced artificial intelligence models, particularly DNN, provides an effective approach for estimating rapeseed AGB. [ABSTRACT FROM AUTHOR]

A32 kDa protein from fungi can be used to produce nanoparticles which might be use as nanofertilisers needed by plants. There are large numbers of fungi which can be used for the efficient synthesis of nanofertiliser particles. Generally, the formation of nanoparticles by fungi involves metal capture, enzymatic reduction and capping on their surface. Metal ions are located either on the outer surface or inside fungal cells and then chemically reduced to nanoparticles in the presence of fungal enzymes. The best way to apply fungus-synthesised nanoparticles/nanofertiliser is to foliage but they can also be applied to soil or through seed soaking. They may also apply through drip, sprinkler, hydroponic, aeroponic and aquaponic. The major effects of nanoparticles as nanofertilisers are on the elevation of antioxidant enzyme activities and photosynthetic pigments. They help to improve in plant tolerance to stresses and defence against pest and diseases after retaining important physiological and biochemical functions. The net results are increased seed germination, vigour index, chlorophyll level, hormonal regulation, photosynthetic rate, electrolytic levels, plant biomass and crop yields. Mycoprotein nanoparticles may alter plant metabolic pathways, regulating energy dissipation, and improved membrane permeability and stability, at the same time as increasing plant health and growth kinetic traits. They are also known to trigger to produce more microbial polysaccharide from polysaccharide secreting fungi that help in soil aggregation, moisture retention, carbon build - up. However, they should be applied only in recommended doses to avoid adverse effects on plant growth and toxicity [ABSTRACT FROM AUTHOR]

Large-scale land acquisitions in Africa are increasing, reported often as the transfers of land for food and biofuel crop production. Only reporting agricultural acquisitions underplays potential impacts of other forms of acquisitions like tourism and conservation, which are new engines for economic growth in Southern Africa. While this shift has complex social-ecological implications, there is limited evidence of the multiple ways that land acquisitions unfold in wetland ecosystems, and implications for people and nature. This study aims to investigate local perceptions of implications of land and water acquisitions on local livelihoods in the Okavango Delta, Botswana, using in-depth interviews with 116 local respondents in Etsha 6, Khwai and Tubu villages. Findings revealed that the primary drivers of land acquisitions in the Okavango Delta were tourism and subsistence agriculture, and a new and unique land exchange (we termed land borrowing) was prevalent in Tubu, involving the borrowing of farmland in flood recessions between locals. Concessions, borrowings, and rentals were key perceived land acquisition types. Both positive and negative impacts of land acquisitions on livelihoods surfaced. The diversity of cultural grouping influenced locals' intricate connection with riparian waters and affected how land was exchanged and governed. The disparities in benefits from land resources have negative implications for equitable resource distribution and natural resource governance, in policy and practice. This research highlights the importance of an expanded view of acquisitions and associated impacts with closer attention to power dynamics which can facilitate more nuanced implementation of targets of the Kunming–Montreal Global Biodiversity framework. [ABSTRACT FROM AUTHOR]

Cytochrome b6f complex is a thylakoid membrane-localized protein and catalyses the transfer of electrons from plastoquinol to plastocyanin in photosynthetic electron transport chain. In the present study, Cytochrome b6 (KaCyt b6) gene from Kappaphycus alvarezii (a red seaweed) was overexpressed in tobacco. A 935 base pair (bp) long KaCyt b6 cDNA contained an open reading frame of 648 bp encoding a protein of 215 amino acids with an expected isoelectric point of 8.67 and a molecular mass of 24.37 kDa. The KaCyt b6 gene was overexpressed in tobacco under control of CaMV35S promoter. The transgenic tobacco had higher electron transfer rate and photosynthetic yield over wild-type and vector control tobacco. The KaCyt b6 tobacco also exhibited significantly higher photosynthetic gas exchange (PN) and improved water use efficiency. The transgenic plants had higher ratio of PN and intercellular CO2. The KaCyt b6 transgenic tobacco showed higher estimates of photosystem II quantum yield, higher activity of the water-splitting complex, PSII photochemistry, and photochemical quenching. The basal quantum yield of nonphotochemical processes in PSII was recorded lower in KaCyt b6 tobacco. Transgenic tobacco contained higher contents of carotenoids and total chlorophyll and also had better ratios of chlorophyll a and b, and carotenoids and total chlorophyll contents hence improved photosynthetic efficiency and production of sugar and starch. The KaCyt b6 transgenic plants performed superior under control and greenhouse conditions. To the best of our knowledge through literature survey, this is the first report on characterization of KaCyt b6 gene from K. alvarezii for enhanced photosynthetic efficiency and growth in tobacco. [ABSTRACT FROM AUTHOR]

Biochar amendment improves crop yield and mitigates climate change, but the lasting effect of biochar application on crop and soil properties under water scarcity conditions in tropical soils remains unexplored. We examined how a one-time biochar application alone and co-applied with vermicompost, with application rates of 25 and 50 ton ha−1, affected the growth of Zea mays L. and the related physicochemical and hydraulic properties of a clay soil after three years. Analyses included pH, electrical conductivity, the availability of cations and phosphorous, carbon to nitrogen ratio, soil water characteristics, crop growth and biomass. The results showed that 50 ton ha−1 of biochar co-applied with vermicompost produced more beneficial effects on the maize crop than 25 ton ha−1 biochar, in the first cycle and to a lesser extent in the third cropping season, caused mainly by the availability of phosphorous and potassium, and the enhancement of bulk density, porosity, and moisture retention. Our results suggest that a one-time application of biochar combined with vermicompost enhances maize growth under limited water conditions. However, further research is necessary to understand the long-term effect of biochar on the soil structure of clay soils, crucial for effectively managing crops in water-scarce conditions. [ABSTRACT FROM AUTHOR]

SUMMARY: Lipid droplets (LDs) are unusual organelles that have a phospholipid monolayer surface and a hydrophobic matrix. In oilseeds, this matrix is nearly always composed of triacylglycerols (TGs) for efficient storage of carbon and energy. Various proteins play a role in their assembly, stability and turnover, and even though the major structural oleosin proteins in seed LDs have been known for decades, the factors influencing LD formation and dynamics are still being uncovered mostly in the "model oilseed" Arabidopsis. Here we identified several key LD biogenesis proteins in the seeds of pennycress, a potential biofuel crop, that were correlated previously with seed oil content and characterized here for their participation in LD formation in transient expression assays and stable transgenics. One pennycress protein, the lipid droplet associated protein‐interacting protein (LDIP), was able to functionally complement the Arabidopsis ldip mutant, emphasizing the close conservation of lipid storage among these two Brassicas. Moreover, loss‐of‐function ldip mutants in pennycress exhibited increased seed oil content without compromising plant growth, raising the possibility that LDIP or other LD biogenesis factors may be suitable targets for improving yields in oilseed crops more broadly. [ABSTRACT FROM AUTHOR]

Preemergence herbicide application under plastic mulch is an effective way to manage weeds in tomato (Solanum lycopersicum L.) production. Nonetheless, applying herbicides beneath plastic mulch in raised beds is associated with the inherent risk of crop phytotoxicity. This highlights the need to explore crop-safe methods for herbicide application in plastic mulch beds. The research aimed to evaluate the effectiveness of preemergence herbicides S-metolachlor and flumioxazin at the labeled rate (X) and reduced rate (0.5X, half of the labeled rate) either alone or in combination with a super absorbent polymer, soil binding agent, or compost to determine their ability to control weeds effectively in plastic mulched beds without causing negative effects on tomato crops. Two different experimental trials, trial 1 (Mar-Jun 2021) and trial 2 (Oct 2021-Jan 2022) were performed in the fields in Immokalee, FL, USA. The experimental design was a randomized complete block with five replications. S-metolachlor (X) plus soil binding agent and S-metolachlor (X) plus compost mix suppressed purple nutsedge density by >85% and approximately 68%, respectively, during trial II. Similarly, S-metolachlor (X), S-metolachlor (0.5X) plus super absorbent polymer, S-metolachlor (X) plus super absorbent polymer, S-metolachlor (X) plus soil binding agent, and S-metolachlor (X) plus compost caused reductions in purple nutsedge biomass by >50% compared with that of the nontreated control during trial II. Treatments did not significantly impact tomato crop vigor and chlorophyll contents during trials I and II. Moreover, treatments did not significantly affect tomato crop biomass and yield during both trials. In summary, using preemergence S-metolachlor (X) combined with soil binding agent or compost could be a viable option for suppressing purple nutsedge in plastic mulched tomato beds. [ABSTRACT FROM AUTHOR]

This article presents an energy-efficient biochar kiln that produces biochar from agricultural crop residues. The kiln is designed to be easy to operate and has minimal requirements for special operations. It works by heating biomass in a combustion chamber using recirculated pyrogas. The study optimized the process parameters and economics of producing biochar from wheat straw using Response Surface Methodology (RSM) based on Central Composite Design (CCD). The sustainable pyrolyzer had a thermal efficiency of 43.69%, with steady-state operation at 517.68 ± 98.18 °C. It produced an average of 54.57 ± 1.86 kg of biochar per batch, using 36.96 ± 3.66 kg of subabul (Leucaena leucocephala) as fuel and 179.61 ± 2.87 kg of wheat straw as feedstock. Subabul is chosen as a fuel due to its rapid growth, high calorific value, low moisture content, efficient combustion, and minimal smoke emission. The thermogravimetric index (TGI) and calorific value of WSB were 7.14 and 25.91 ± 0.74 MJ/kg, respectively. The benefit–cost ratio and payback period were 2.27 ± 0.16 and 4.92 ± 0.44 months, respectively. [ABSTRACT FROM AUTHOR]

Introduction: Satellite-sourced data have become a valuable resource for precision agriculture because they provide crucial insights into various parameters that are essential for effective crop management. An array of practical agricultural tools provides comprehensive data for assessing crop biomass, soil conditions, and plant stress symptoms, predicting yields, and performing other functions. Satellite data, when combined with in situ data from different sources, can significantly enhance biomass and yield estimations. Material and Methods: The ability of the "PROcesses of radiation, Mass and Energy Transfer" (PROMET) model to predict crop biomass and grain yield and to optimize nitrogen fertilization during the vegetation period was investigated. Field trials were conducted to assess the accuracy and limitations of biomass and yield predictions. Results and Conclusion: The predicted yields were sufficiently accurate on a whole-field basis, and site-specific values showed strong correlations. In additional field trials with different fertilization strategies, the highest yield and nitrogen efficiency were observed for the PROMET-based strategy. Additional experiments with different crops and greater durations are needed to draw a more reliable conclusion. [ABSTRACT FROM AUTHOR]

Critical influence of different level of shade on the underlying physiological and biophysical limitations of an important pulse crop pigeonpea [(Cajanas cajan (L.)] has been investigated. The crop was grown under three level of shade intensity 33% (S1), 50% (S2), 75% (S3) based on the incident sunlight intensity as obtained through providing different category of shade-net in shade-net house facilities and the open field (open) without shade. Major impact has been observed on photosynthetic CO2 assimilation (Amax), leaf water use efficiency (WUEi), photosynthetic radiation use efficiency (PRUE) and biophysical constraints relating to photosynthetic light energy utilization. Efficiency of the crop for light energy utilization has been assessed through chlorophyll fluorescence traits for Photosystem II (PSII) functioning, leaf level physio-biophysical indicators and the leaf spectral traits. The functional traits were responsible for the critical impact of shade causing limitation to get maximum potential performance of the crop. Amax was noted 22.58 µ mol CO2 m−2 s−1 in open sun light grown plants (Open) whereas, 19.91, 13.03 and 7.20 at S1, S2 and S3 level of shade respectively. In comparison to open, transpiration rate (E) declined by only 4.6% at S1 level of shade whereas it substantially decreased by 44.4% and 68.3% at S2 and S3 level of shade respectively. Differential reduction in the physiological and leaf biophysical responses depending on the intensity of shade suggested that the physiological functioning of the crop has been progressively diminished over and above the S1. Electron transport rate across PSII (ETR) marginally reduced at S1 by 10.65% while it progressively decreased at S2 (31.07%) and S3 (55.17%) level of shade in comparison to open. The findings have clearly revealed that the limitation of electron supplies through PSII and their inefficient utilization for driving the photosynthetic carbon acquisition were the major limiting factors for achieving the potential performance of the crop under shade. The results would be useful for searching for better crop to cope with the limitation of shade through achieving shade-tolerance or shade-resilience in crops for agroforestry importance. The present work offers a perspective as to how different intensity of shades impair the various aspects involving the important pulse crop i.e. pigeonpea which will further improve our understanding of the functional importance of the physiological and biophysical processes involved to alleviate the major constraints posed by shade. Further, the present study has revealed that about 33% shade (S1) based on the incident sun light, can be a critical limit for the crop as the deep (S2) and extreme (S3) shade has highly detrimental effects on the physiology of the crop which remarkably affects the grain yield production. [ABSTRACT FROM AUTHOR]

Rice is a staple food in Asia, and its impact on the environment is considerable, such as chemical input concerns. Organic rice farming represents an alternative approach to reducing environmental concerns throughout rice production. However, the precise nutrient management to optimize organic rice production while recovering soil residual nitrogen (N) for the subsequent crops remains unclear. This study aims to: (1) assess nutrient recovery in soil cultivated with cover crops, including Italian ryegrass and hairy vetch, and (2) investigate the optimization of nutrient management in organic rice farming using cover crops. An experiment was conducted in a paddy field adopting cover crop plots and fallow (FA) plots in four replicates each from 2021 to 2023. In addition, incubation studies were conducted in 2021 and 2022. The incubation study included various treatments: (1) soil from cover crop or FA plots, (2) with or without cover crop residues, (3) with or without weed input (2021). In 2022, fertilizer input replaced weed input. The field study indicated cover crop biomass was larger than that of weeds. Furthermore, it can determine cover crops have more recyclable plant N compared to weeds when incorporated into the soil. In contrast, there was no noticeable difference in soil inorganic N and soil total organic carbon (C) contents between cover crop and FA plots at the 0–90 cm depth. In the incubation study, we found the soil of cover crop plots and cover crop input show less inorganic N than the soil of FA plots and cover crop input during the incubation period. However, the soil of the cover crop plots and cover crop input showed a high inorganic N content after setting the flooded condition. It indicates the soil of cover crop plots, and cover crop input provides N to the soil for a longer period. Overall, our results show that winter cover crop application in paddy fields contributes to N recovery and helps maintain soil fertility. Specifically, the occasional cultivation of a combination of Italian ryegrass and hairy vetch as winter cover crops can contribute to reducing the reliance on chemical fertilizers. This practice also promotes sustainable rice farming in paddy fields. [ABSTRACT FROM AUTHOR]

Cover crops protecting soil erosion during the summer fallow in the monsoon weather may enhance dryland winter wheat yield and N relations. We examined the effects of four summer cover crops (soybean (Glycine max L., SB), sudangrass (Sorghum sudanense {Piper} Stapf, SG), soybean and sudangrass mixture (SS), and no cover crop (CK)) and three N fertilization rates (0, 60, and 120 kg N ha−1) on winter wheat yield, quality, and N relations from 2017–2018 to 2020–2021 in the Loess Plateau of China. Cover crop biomass and N accumulation, soil mineral N, and winter wheat yield, protein concentration, and N uptake were greater for SB and SS than other cover crops at most N fertilization rates and years. The N fertilization rate had variable effects on these parameters. Winter wheat aboveground biomass and grain N productivities were greater for CK than other cover crops at all N fertilization rates and years. Nitrogen balance was greater for SS than other cover crops at 60 and 120 kg N ha−1 in all years. The SS with 120 kg N ha−1 can enhance soil mineral N, winter wheat yield and quality, and N balance compared to CK and SG with or without N fertilization rates. [ABSTRACT FROM AUTHOR]

Mulch from cover crops can suppress weeds and facilitate organic no‐till corn and soybean production. However, research is lacking on the no‐till planting small grain crops into rolled‐crimped cover crops. An experiment was conducted to test the effects of no‐till planting winter wheat (Triticum aestivum L.) into five cover crops planted in early summer, mid‐summer, and late summer. Cover crops were terminated with a roller‐crimper, and winter wheat was simultaneously no‐till planted in early fall. A "no cover crop" control treatment was also included, where wheat was planted into tilled soil. Cover crop and weed biomass at wheat planting varied by cover crop planting date and species. Early‐summer‐planted sorghum sudangrass [Sorghum bicolor (L.) Moench × S. sudanense (Piper) Stapf.] produced the most cover crop biomass and had among the lowest weed biomass at wheat planting and wheat harvest. However, wheat seedling density and grain yield were relatively low in the early‐planted sorghum sudangrass treatment compared with the other cover crop treatments, indicating a tradeoff between weed suppression and wheat yield. Early‐planted buckwheat (Fagopyrum esculentum Moench) and early‐planted soybean [Glycine max (L.) Merr.] had among the highest wheat grain yields, but no treatments yielded more than the "no cover crop" control. Wheat grain nitrogen was variable and may have been impacted by multiple factors, including wheat density. Results from this experiment indicate that rolled‐crimped cover crops can facilitate organic no‐till winter wheat production, but more research is needed to overcome tradeoffs and optimize production. Core Ideas: Examined organic winter wheat that was no‐till planted into different cover crops planted at different times.Increasing cover crop biomass suppressed weeds, but treatments with high biomass reduced wheat density and yield.Wheat yields in the early‐planted buckwheat and soybean treatments were comparable to the "no cover crop" control.No‐till planting wheat into rolled‐crimped cover crops can reduce tillage without impacting yield. [ABSTRACT FROM AUTHOR]

Soil aggregation plays a critical role in the maintenance of soil nutrient storage and supply. After five years of crop biomass management, field samples from a sandy loam mountain hilly soil were examined for aggregate distribution, physical subfractions within aggregates, and organic nitrogen (N) fractions, such as nonhydrolyzable N (NHN), hydrolysable ammonium N (HAN), amino-sugar N (ASN), amino-acid N (AAN), and hydrolysable unidentified N (HUN). The total N pool and theoretically mineralizable N were used to calculate the soil N storage and supply capacity, respectively. The total N, mineralizable N, and coefficient of mineralisation rate were all considerably raised by crop biomass incorporation. Analysis of covariance structures showed that the organic N fractions had an impact on the supply and storage of N in the soil, with HUN and AAN contributing the most to the potentially mineralizable N and; also HUN and AAN making up the largest portion of the total soil N pool. In comparison to bulk soils that had not had biomass removed, the amounts of organic N components HAN, ASN, AAN, HUN, and NHN were higher by 98.2%, 87.2%, 71.47%, 38.91%, and 43.27%, respectively. Compared to microaggregates, biomass incorporation enhanced soil macroaggregates by 9.37% and had higher organic N percentages and accumulation efficiency. The mineralizable N was significantly correlated with all fractions of N. The inorganic nitrogen and total nitrogen (TN) were higher in 100% biomass inclusion-T5 (60.01 and 841.58) and lowest in total removal of biomass-T1 (24.92 and 479.74). The > 2 mm aggregate size significantly contributed more in organic N fractions rather than 2–0.25 mm or less. [ABSTRACT FROM AUTHOR]

Bioenergy is considered the largest contributor to the renewable and sustainable energy sector worldwide, playing a significant role in various energy sectors such as heating, electricity supply, and even in replacing fossil fuels in the transportation sector. As part of renewable, low-carbon energy systems, bioenergy can also ensure atmospheric carbon sequestration, provide numerous environmental and socio-economic benefits, and thus contribute to achieving global climate change goals, as well as broader environmental, social, economic, and sustainable development objectives. The use of bioenergy can significantly reduce our carbon footprint and thus contribute to improving the environment. While bioenergy conversion of biomass produces some amount of carbon dioxide, similar to traditional fossil fuels, its impact can be minimized by replacing forest biomass with fast-growing trees and energy crops. Therefore, fast-growing trees and energy crops are the primary raw materials for bioenergy. The results of the research in this publication confirm the high efficiency of biomass depolymerization through thermochemical conversion. The principle of continuous biomass conversion was used at a process temperature of 520 °C. The experiments were carried out in the Biomass Gasification Laboratory at the AgroBioTech Research Center of the Slovak University of Agriculture in Nitra. The biomass used for the experiments was from energy-producing fast-growing willows, specifically the varieties Sven, Inger, and Express. The aim was to determine the amount of biochar produced from each of these tree species and subsequently to investigate its potential use for energy purposes. During the experiments, 0.106 kg of biochar was produced from 1 kg of Inger willow biomass, 0.252 kg from 1 kg of Express willow biomass, and 0.256 kg from 1 kg of Sven willow biomass. A subsequent goal was to determine the production of gas, which can also be used for energy purposes. The biofuel samples obtained were subsequently subjected to thermogravimetric analysis to determine moisture content, volatile matter, and ash content. The ash content in dry matter ranged from 6% to 7.28%, while the volatile matter in dry matter was between 92.72% and 94%. The moisture content in the samples ranged from 1.7% to 2.43%. These results may contribute to innovative insights into biomass depolymerization and help define optimized parameters for thermochemical conversion, as well as the required biomass composition, with the goal of generating second-generation biofuels in the most cost-effective way. [ABSTRACT FROM AUTHOR]

In the Middle Atlas rangelands, traditional methods for estimating standing crop biomass are labour-intensive and impractical. Remote sensing offers an initiative for standing crop biomass large-scale monitoring. The aim of this study was to estimate standing crop biomass, comprising annual and perennial forbs, grasses and perennial shrubs, using remote sensing data. The vegetation indices (NDVI, DVI, RVI, MSAVI and OSAVI) were derived from medium-resolution Landsat 8 and MODIS imagery. Sixty sampling sites were used for the biomass data collection. These sites were located across three grazing areas and data were collected in May and June 2016. Regression models were established between biomass field data and the five indices. Correlation analysis indicated that among the five vegetation indices, only DVI had the lowest value (r = 0.60). Linear models developed between the biomass field data and vegetation indices showed that NDVI, OSAVI and RVI explained a reasonable percentage of the variance in biomass. Values for R2 were 0.74, 0.77 and 0.71, respectively. Among these indices, the OSAVI performed better, with a high R2 and low error (MAPE = 11.03%). The established models represent a key tool for long-term monitoring of these rangelands. [ABSTRACT FROM AUTHOR]

This long-term field study conducted in Yancheng, China, evaluated the effects of diverse crop rotation sequences on rice growth, yield, and soil properties. Six rotation treatments were implemented from 2016 to 2023 as follows: rice–wheat (control), rice–rape, rice–hairy vetch, rice–barley, rice–faba bean, and rice–winter fallow. Rice growth parameters, yield components, biomass accumulation, and soil properties were measured. Results showed that legume-based rotations, particularly rice–faba bean and rice–hairy vetch, significantly improved rice growth and yield compared to the rice–wheat control. The rice–faba bean rotation increased yield by 19.1% to 8.73 t/ha compared to 7.33 t/ha for the control, while rice–hairy vetch increased yield by 11.9% to 8.20 t/ha. These rotations also demonstrated higher biomass production efficiency, with increases of 33.33% and 25.00%, respectively, in spring crop biomass. Soil nutrients improvements were observed, particularly in available nitrogen, potassium, and electrical conductivity. Legume-based rotations increased the available nitrogen by up to 35.9% compared to the control. The study highlights the potential of diversified crop rotations, especially those incorporating legumes, to enhance rice productivity and soil health in subtropical regions. These findings have important implications for developing sustainable and resilient rice-based cropping systems to address challenges of food security and environmental sustainability in the face of climate change and resource constraints. [ABSTRACT FROM AUTHOR]

Biomass energy is increasingly recognized as a promising alternative to conventional energy sources, offering potential sustainability and environmental benefits. Miscanthus has emerged as a standout candidate within energy crops, with M. lutarioriparius particularly noteworthy. This research delves into the intricate relationship between the timing of harvest and the resulting biomass yield and combustion quality of M. lutarioriparius in the unique coastal wetlands surrounding China's Dongting Lake. An extensive field experiment was meticulously executed to explore these dynamics, yielding valuable insights comprehensively. (1) First and foremost, the study unearthed a paradoxical trend: delaying the harvest of M. lutarioriparius led to an increase in the stem-to-leaf ratio. However, this apparent benefit was counterbalanced by a noticeable decrease in overall biomass yield, primarily driven by the shedding of leaves as harvest was delayed. Delving into the intricacies of biomass composition, delayed harvests had a significant impact. (2) Specifically, they resulted in marked reductions in water content, ash content, and hemicellulose levels within M. lutarioriparius biomass. The correlation analysis further underscored the importance of cellulose and lignin, with a strong positive relationship between their content and calorific value, while hemicellulose exhibited a highly significant negative correlation. (3) Additionally, the study ventured into the realm of mineral elements within the biomass. Delayed harvesting precipitated a substantial reduction in their content, with notable fluctuations observed in potassium (K) and calcium (Ca) levels. Furthermore, ash content exhibited positive correlations with potassium (K) and silicon (Si) contents, shedding light on the intricate interplay of mineral elements. A notable silver lining emerged despite the reduced biomass yield associated with delayed harvesting. In a holistic assessment, the optimal window for harvesting M. lutarioriparius to maximize fuel quality was pinpointed to span from late November to the conclusion of January in the subsequent year. This nuanced understanding of harvesting timing can play a pivotal role in optimizing the utilization of M. lutarioriparius as a valuable energy resource. [ABSTRACT FROM AUTHOR]

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Summary Biomass crops engineered to accumulate energy‐dense triacylglycerols (TAG or ‘vegetable oils’) in their vegetative tissues have emerged as potential feedstocks to meet the growing demand for renewable diesel and sustainable aviation fuel (SAF). Unlike oil palm and oilseed crops, the current commercial sources of TAG, vegetative tissues, such as leaves and stems, only transiently accumulate TAG. In this report, we used grain (Texas430 or TX430) and sugar‐accumulating ‘sweet’ (Ramada) genotypes of sorghum, a high‐yielding, environmentally resilient biomass crop, to accumulate TAG in leaves and stems. We initially tested several gene combinations for a ‘push‐pull‐protect’ strategy. The top TAG‐yielding constructs contained five oil transgenes for a sorghum WRINKLED1 transcription factor (‘push’), a Cuphea viscosissima diacylglycerol acyltransferase (DGAT; ‘pull’), a modified sesame oleosin (‘protect’) and two combinations of specialized Cuphea lysophosphatidic acid acyltransferases and medium‐chain acyl‐acyl carrier protein thioesterases. Though intended to generate oils with medium‐chain fatty acids, engineered lines accumulated oleic acid‐rich oil to amounts of up to 2.5% DW in leaves and 2.0% DW in stems in the greenhouse, 36‐fold and 49‐fold increases relative to wild‐type (WT) plants, respectively. Under field conditions, the top‐performing event accumulated TAG to amount to 5.5% DW in leaves and 3.5% DW in stems, 78‐fold and 58‐fold increases, respectively, relative to WT TX430. Transcriptomic and fluxomic analyses revealed potential bottlenecks for increased TAG accumulation. Overall, our studies highlight the utility of a lab‐to‐field pipeline coupled with systems biology studies to deliver high vegetative oil sorghum for SAF and renewable diesel production. [ABSTRACT FROM AUTHOR]

Plants shape their surrounding soil, influencing subsequent plant growth in a phenomenon known as plant–soil feedback (PSF). This feedback is driven by chemical and microbial legacies. Here, we cultivated six crops from two functional groups, i.e., three grasses (Lolium , Triticum , and Zea) and three legumes (Glycine , Lens , and Medicago), to condition a living soil. Subsequently, the same species were sown as response plants on conspecific and heterospecific soils. We employed high-throughput sequencing in tandem with soil chemistry, including total organic matter, pH, total nitrogen, electrical conductivity, phosphorus, and macro and micro-nutrients. Our results showed that Glycine exhibited the strongest negative PSF, followed by Triticum and Zea , while Lolium displayed low feedback. Conversely, Lens demonstrated robust positive PSF, with Medicago exhibiting slight positive feedback. Soil chemistry significance indicated only higher Cl content in Triticum soil, while Lens displayed higher Zn and Mn contents. Microbial diversity exhibited no significant variations among the six soils. Although conditioning influenced the abundance of functionally important microbial phyla associated with each plant, no specificity was observed between the two functional groups. Moreover, each crop conditioned its soil with a substantial proportion of fungal pathogens. However, co-occurrence analysis revealed a strong negative correlation between all crop's biomass and fungal pathogens, except Glycine , which exhibited a strong negative correlation with mutualists such as Arthrobacter and Bacillus. This underscores the complexity of predicting PSFs, emphasizing the need for a comprehensive understanding of plant interactions with both pathogens and mutualists, rather than focusing solely on host-specific pathogens. [ABSTRACT FROM AUTHOR]

The rapid depletion of conventional fuel resources and rising energy demand has accelerated the search for alternative energy sources. Further, the expanding need to use bioenergy crops for sustainable fuel production has enhanced the competition for agricultural land, raising the "food vs. fuel" competition. Considering this, producing bioenergy crops on marginal land has a great perspective for achieving sustainable bioenergy production and mitigating the negative impacts of climate change. C4 crops are dual-purpose crops with better efficiency to fix atmospheric CO 2 and convert solar energy into lignocellulosic biomass. Of these, millets have gained worldwide attention due to their climate resilience and nutraceutical properties. Due to close synteny with contemporary C4 bioenergy crops, millets are being considered a model crop for studying diverse agronomically important traits associated with biomass production. Millets can be cultivated on marginal land with minimum fertilizer inputs and maximum biomass production. In this regard, advanced molecular approaches, including marker-assisted breeding, multi-omics approaches, and gene-editing technologies, can be employed to genetically engineer these crops for enhanced biofuel production efficiency. The current study aims to provide an overview of millets as a sustainable bioenergy source and underlines the significance of millets as a C4 model to elucidate the genes and pathways involved in lignocellulosic biomass production using advanced molecular biology approaches. • Millets, being C4 crops, are considered a model for studying agronomically and economically important traits. • Millets hold great potential as future bioenergy crops due to their climate resilience trait and high water use efficiency. • Millets can be cultivated on marginal land with minimum fertilizer inputs which is essential for resource optimization. • Advanced molecular approaches can help to genetically engineer these crops for optimized biofuel production efficiency. [ABSTRACT FROM AUTHOR]

Background: This study is meant to examine the energy requirement and energy input- output of different cropping sequences. The crucial objective to conduct experiment to understand energy efficiency using inputs and outputs which were disbursed in cropping sequences. Hence, it is need of the hour to identify the most remunerative and cost effective cropping sequence with high energy efficient for UGP of India. Methods: This study was carried out at the research farm of ICAR-Indian Institute of Farming Systems Research, Modipuram, during 2017-2021. The divergent cropping sequences viz. sugarcane-ratoon-wheat (CS1); rice-wheat-dhaincha (CS2); pigeonpea + maize-chickpea-okra (CS3); maize-berseem-black gram (CS4); sorghum-mustard-green gram (CS5) and Napier+cowpea/berseem (CS6) were compared in reference to curtail higher energy inputs through selected alternate cropping sequences. The obtained energy values were calculated by multiplying the amount of inputs and outputs by using energy conversion factors. Result: Maximum inputs energy consumed by sugarcane crop alone (33.14x10³ MJ ha-1). Results shown that irrigation, seed, fertilizers and diesel required higher energy for the completion of cultural operations. However, higher inputs energy was used in irrigation followed by seed and fertilizers, respectively. In regard to per cent energy intake through inputs, the highest energy spent was for irrigation (35.30 MJ ha-1) and fertilizer (23.80 MJ ha-1). The wheat equivalent yield was higher in sugarcane-ratoon-wheat (125.58 t ha-1). Maximum output energy was with above system (596.70x10³ MJ ha-1). Highest net energy returns was counted with sugarcane-ratoon-wheat (549.37x10³ MJ ha-1), energy ratio (12.60) and energy profitability (11.60). Indeed, energy efficiency was highest in same system (1657.50) followed by maize-berseem-black gram (1421.96). [ABSTRACT FROM AUTHOR]

Cover crops and nitrogen (N) fertilization may affect soil mineral N, N uptake, and N productivity (grain yield per unit plant available N) in wheat (Triticum aestivum L.). We evaluated the effect of summer cover crops and N fertilization rates on soil mineral N and winter wheat grain yield, N uptake, and N productivity in the Loess Plateau of China. We measured cover crop aboveground biomass N, soil mineral N (0-20 cm), and winter wheat yield, N uptake, and N productivity for four seasons from 2017-2018 to 2020-2021. Cover crops were soybean (Glycine max L., SB), sudangrass (Sorghum sudanense [Piper] Stapf, SG], soybean and sudangrass mixture (SS), and no cover crop (CK) and N fertilization rates were 0, 60, and 120 kg N ha−1 applied to wheat. The SB increased cover crop biomass N and soil mineral N by 15 to 65%, but SS increased winter wheat yield, protein concentration, and N uptake by 25 to 55% compared to SG and CK at most N fertilization rates and years. Nitrogen fertilization rate had a variable effect on cover crop and wheat parameters. Wheat N productivity was 55 to 85% greater with CK than cover crops, but decreased with increased N fertilization rates. The N fertilizer equivalence of cover crops for wheat yield and N uptake ranged from 31 kg N ha−1 for SG to 150 kg N ha−1 for SS. Overall, SS with 60 kg N ha−1 can sustain winter wheat N uptake and N productivity compared to SG or CK with or without N fertilization. [ABSTRACT FROM AUTHOR]

Food is important for long-term national peace and stability. Land, water, and energy are essential resources that support food production. Conflicts among economic, social, and environmental objectives are inevitable in agricultural systems. On the basis of the concept of the water‒energy‒food (WEF) nexus, this study presents an interval multiobjective nonlinear optimization model to balance the conflicts of agricultural systems. This optimization model is then applied to Jiangsu Province to verify its applicability. Using the model, the optimal allocation of land, water, and energy and the corresponding system benefits under ten scenarios are obtained. The results show that wheat has the largest planting area when the decision is biased toward economic objectives. Planting more rice can improve the environment, and planting less rice can strengthen social fairness. The water and energy allocated to crops gradually decrease as decision-making preferences shift from the economy to society and the environment. The results also indicate that the comprehensive scores under scenario S4 (society → environment → economy) reached the ideal state among the seven multiobjective scenarios. Compared with the control year (2020), the optimal total land allocation in scenario S4 is reduced by 17.49%-17.84% to ensure food security. Notably, economic profits decrease by 6.68%-38.6%, social fairness significantly improves by 45.39%–55.62%, and total carbon emissions decrease by 8.88%–25.78%. This study can help decision-makers obtain a management scheme for maximizing comprehensive interests in the agricultural WEF nexus system. [ABSTRACT FROM AUTHOR]

The relationship between precipitation and evapotranspiration (ET) is critical to understanding water cycle related dynamics in ecosystems, including crops. Existing studies of bioenergy crops have primarily focused on annual or seasonal ET rates, with less attention given to the immediate ET response following precipitation events. This study examines the variation in ET rates in the days subsequent to precipitation events across various bioenergy crops—corn, switchgrass, and prairies—utilizing 13 years (2010–2022) of growing season data. Meteorological and eddy covariance flux data were collected from seven eddy covariance flux towers as part of the GLBRC scale-up experiment at the Kellogg Biological Station Long Term Ecological Research sites. The analysis revealed that average ET peaked the day after precipitation and declined linearly over the following days, with a statistically significant relationship (p -value = 0.00027, R2 = 0.96). Neither the type of biofuel vegetation nor the historical land use significantly influenced ET post-precipitation events (p -values = 0.53 and 0.153, respectively). Key predictors of ET following precipitation events include shortwave radiation, season, day of the year, ambient temperature, vapor pressure deficit (VPD), long-wave radiation, precipitation amount, soil moisture, and annual variability. These findings enhance our comprehension of ET responses in bioenergy crop systems, with implications for water management in sustainable agriculture. [ABSTRACT FROM AUTHOR]

The sorghum × sudangrass hybrid is significant as a biofuel crop due to its high biomass production, drought tolerance, adaption ability to various climatic conditions, and high sugar content in its stems. This study aimed to determine the effects of six different nitrogen dose treatments on ethanol yield, yield parameters, and fertilizer use relationships in sorghum × sudangrass hybrid plants in two locations in 2021 and 2022. The experiment was established according to the randomized block design with three replicates. Nitrogen treatments were applied as N0 (0 kg da-1), N5 (5 kg da-1), N10 (10 kg da-1), N15 (15 kg da-1), N20 (20 kg da-1), and N25 (25 kg da-1). Juice ethanol yield (JEY), lignocellulosic ethanol yield (LEY), and theoretical ethanol yield (TEY) values varied between 123.8-219.0 L da-1, 522.2-955.1 L da-1, and 646.0-1174.2 L da-1, respectively. JEY, LEY, and TEY values increased as the amount of nitrogen increased. The correlation analysis found a high positive relationship between all traits except acid detergent lignin. As a result of the orthogonal comparison, it was found that the nitrogen dose amount should be increased for JEY, LEY, and TEY. Principal components-biplot analyses explained 92.9% of the relationships between the studied parameters and the nitrogen dose levels. This study, conducted over two years and in two locations, determined that sorghum x sudangrass hybrid cultivation could be realized in terms of bioethanol yield under different nitrogen dose levels and that the ethanol yield potential is high. [ABSTRACT FROM AUTHOR]

In this study, the changes in yield, nutrient content, and amino acid levels in legume–cereal grass mixtures were qualitatively evaluated depending on the legume–cereal combination and inoculation with preparations based on Rhizobium. This study, taking into account the biological characteristics of legume forage crops, used inoculations with strains of nodule bacteria and associative nitrogen fixers to enhance the process of the nitrogen fixation of mixed crops of legumes and cereal. The aim of this study was to compare the yields and nutritional values of monocultures and mixed crops, as well as to determine the effects of preparations based on strains of nodule bacteria and the associated nitrogen fixer on the photosynthetic activity and yield of combined annual legume–grain crops. A comparative study of forage crop biomass was conducted to analyze crude protein, fiber, carotene, and amino acid content in monocultures and legume–cereal mixtures, with and without the use of nodule-bacteria-based preparations (Rhizotorphin, Mizorine, Flavobactrin, and Azolene). The combined effect of crop mixtures and biological products led to increased green mass yield, protein content, and feed productivity. Notably, two-component mixtures with Rhizotorphin inoculation increased green mass yield by 8.79%, while three-component mixtures saw a 16.49% increase. The oat–pea mixture showed the most significant amino acid improvements, with lysine increasing by 6.26% and tyrosine by 3.24%. The general conclusion reached by the two-year experiment of 2022–2023 in the hill–plain zone of northern Kazakhstan is that double grass mixtures treated with nodule bacteria are more productive than monoculture crops in this area. These results suggest that inoculation with bacterial strains can effectively enhance the productivity of forage crops in northern Kazakhstan, providing a basis for future recommendations on optimizing herbaceous crop combinations. It is recommended to grow annual forage crops in mixtures with legumes to produce highly nutritious feeds with high metabolic energy in terms of biochemical composition. [ABSTRACT FROM AUTHOR]

Brassica carinata A. Braun (carinata) has become an important oil crop for biofuel production in subtropical regions. Carinata is highly sensitive to acetolactate synthase (ALS)‐inhibiting herbicides, limiting its introduction into existing crop rotations. The objective of the study was to develop carinata lines resistant to ALS‐inhibiting herbicides. A susceptible carinata line was crossed with a resistant Brassica napus L. line. Lines derived from those crosses were screened at high doses of imidazolinones, which allowed identifying five lines with high levels of resistance. Doses to reduce plant growth 50% (GR50) and cause 50% injury (ID50) were four to nine times greater than susceptible lines. Resistant lines exhibited cross resistance with halosulfuron (sulfonylurea). Resistance was confirmed under field conditions with doses 2X and 4X for imazethapyr and 4X–8X for halosulfuron of their respective label doses. While susceptible lines died, resistant lines exhibited no injury or growth reductions compared with nontreated controls. Sequencing of the ALS gene indicated that all resistant lines carried a Trp574Leu amino acid substitution, a mutation responsible for resistance in other species. Crosses between resistant lines and a susceptible line demonstrated that the inheritance of the mutation corresponded with the resistance phenotype in the F2. The resistance trait behaved as a single, fully dominant allele, which makes it easier to transfer it to carinata lines with desirable agronomic traits. The resistant lines developed here provide flexibility for use in multiple crop rotations and opens the possibility to use ALS‐inhibiting herbicides for weed control within this crop's growing season. Core Ideas: Brassica carinata is a new crop for biofuel production.Proper integration of this crop to existing rotations is critical.High sensitivity to herbicides used in other crops in the rotation is a major limitation for adoption.Acetolactate synthase (ALS)‐resistant B. carinata lines were developed to avoid injury and increase weed control options in this crop.ALS‐resistance will increase the number and type of crop rotations in which B. carinata can be included. Plain Language Summary: Brassica carinata A. Braun (carinata) is a new crop for biofuel production. Carinata is highly sensitive acetolactate synthase (ALS)‐inhibiting herbicide with long soil residual activity, and this has become a major limitation for growers' adoption. Having lines that are not affected by those herbicides will provide flexibility for rotating carinata with other crops. The objective of the study was to develop carinata lines resistant to ALS‐inhibiting herbicides. Screening carinata germplasm for reduced sensitivity to imazethapyr, an ALS‐inhibiting herbicide, allowed identifying five lines with high levels of resistance. The lines exhibited 4X–9X doses compared with susceptible lines. The resistance was confirmed under field conditions. Genetic analysis indicated that the resistance is controlled by a single, fully dominant allele, which makes it easier to transfer it to carinata lines with desirable agronomic traits. [ABSTRACT FROM AUTHOR]

Soil contaminated with petroleum-derived products should be used to cultivate energy crops. One such crop is Zea mays. Therefore, a study was performed to determine the suitability of Zea mays biomass obtained from gasoline-contaminated soil for energy purposes. The analysis included determining the heat of combustion and calorific value of the biomass, as well as the content of nitrogen, carbon, hydrogen, oxygen, sulfur, and ash in the biomass. Additionally, the suitability of vermiculite, dolomite, perlite, and agrobasalt for the phytostabilization of gasoline-contaminated soil was evaluated. It was found that the application of sorbents to gasoline-contaminated soil significantly reduced the severe negative effects of this petroleum product on the growth and development of Zea mays. Gasoline contamination of the soil caused a significant increase in ash, nitrogen, and sulfur, along with a decrease in carbon and oxygen content. However, it had no negative effect on the heat of combustion or calorific value of the biomass, although it did reduce the energy production from Zea mays biomass due to a reduction in yield. An important achievement of the study is the demonstration that all the applied sorbents have a positive effect on soil stabilization, which in turn enhances the amount of Zea mays biomass harvested and the energy produced from it. The best results were observed after the application of agrobasalt, dolomite, and vermiculite on gasoline-contaminated soil. Therefore, these sorbents can be recommended for the phytostabilization of gasoline-contaminated soil intended for the cultivation of energy crops. [ABSTRACT FROM AUTHOR]

The Leaf Area Index (LAI) is a crucial structural parameter linked to the photosynthetic capacity and biomass of crops. While integrating machine learning algorithms with spectral variables has improved LAI estimation over large areas, excessive input parameters can lead to data redundancy and reduced generalizability across different crop species. To address these challenges, we propose a novel framework based on Bayesian-Optimized Random Forest Regression (Bayes-RFR) for enhanced LAI estimation. This framework employs a tree model-based feature selection method to identify critical features, reducing redundancy and improving model interpretability. A Gaussian process serves as a prior model to optimize the hyperparameters of the Random Forest Regression. The field experiments conducted over two years on maize and wheat involved collecting LAI, hyperspectral, multispectral, and RGB data. The results indicate that the tree model-based feature selection outperformed the traditional correlation analysis and Recursive Feature Elimination (RFE). The Bayes-RFR model demonstrated a superior validation accuracy compared to the standard Random Forest Regression and Pso-optimized models, with the R2 values increasing by 27% for the maize hyperspectral data, 12% for the maize multispectral data, and 47% for the wheat hyperspectral data. These findings suggest that the proposed Bayes-RFR framework significantly enhances the stability and predictive capability of LAI estimation across various crop types, offering valuable insights for precision agriculture and crop monitoring. [ABSTRACT FROM AUTHOR]

• Carbon isotope composition (δ13C) variation among J. curcas genotypes is discrete. • Drought-induced changes in δ13C is remarkable in J. curcas. • δ13C may be used as a tool for screening water-use efficient genotypes in J. curcas. Jatropha curcas L. is a non-food crop quoted as a promising natural feedstock for biodiesel production in tropical and subtropical regions. Although an efficient mechanism of drought avoidance through stomatal control of transpiration has been demonstrated in this species, low carbon assimilation and growth rates preclude any advantage of such strategy under water limitation. Two greenhouse experiments were conducted with the objective of investigating varietal differences in water use as the trade-off between carbon isotope composition (δ13C) in different tissues and water use efficiency, in young plants of J. curcas. The first experiment was a survey with seven provenances of J. curcas under non-limiting water availability. There were no significant differences among provenances for leaf gas exchange rates, growth and whole-plant transpiration (T). However, significant effects of provenance and tissue (stem bark or leaf) in δ13C were demonstrated. The provenances CNPAE183 and CNPAE222 were selected for the second experiment, as variations in water use traits and δ13C between the two provenances were observed. Soil water deficit, imposed for 18 days, led to significant physiological, biochemical, and morphological changes. An early and sharp response to water deficit in CNPAE183 as compared to CNPAE222 was observed, as indicated by a 44% higher rate of decrease of T in the former. In addition, water deficit led to increase of δ13C, which was more pronounced in CNPAE222 (13% in young leaves) when compared to CNPAE183 (11% in young leaves). In both provenances, δ13C was less negative in young as compared to mature tissues. Significant and direct correlations between stem bark and leaf δ13C and leaf-level intrinsic water use efficiency were observed. Contrasting results, particularly on T and δ13C, suggest the existence of genetic diversity for water relations and metabolic traits linked to drought tolerance in J. curcas. Using stem bark or leaf δ13C measurements as the basis for large-scale screening of water-use efficient genotypes should be considered. [ABSTRACT FROM AUTHOR]

Microbiomes play a crucial role in plant health, aiding nutrient acquisition and enhancing stress tolerance in C3 and C4 plants. While past microbiome research focused on the C3 model plant Arabidopsis (Arabidopsis thaliana), recent attention has shifted towards C4 food and biofuel crops such as maize, millet, sorghum, switchgrass, and miscanthus. Similar to C3 plant microbiome assembly, C4 plant microbiome assembly is influenced by environmental factors, such as drought and nutrient availability, as well as plant genetics. Root and shoot microbiomes of C4 cereal plants can extend diverse plant phenotypes of agronomic importance, including tolerance to drought and nitrogen stress, and enhanced yield. Foxtail millet, a climate-resilient crop, holds promise as a model for C4 plant microbiome research due to its small, well-annotated genome and versatile genetic resources. Microbiomes provide multiple life-support functions for plants, including nutrient acquisition and tolerance to abiotic and biotic stresses. Considering the importance of C4 cereal and biofuel crops for food security under climate change conditions, more attention has been given recently to C4 plant microbiome assembly and functions. Here, we review the current status of C4 cereal and biofuel crop microbiome research with a focus on beneficial microbial traits for crop growth and health. We highlight the importance of environmental factors and plant genetics in C4 crop microbiome assembly and pinpoint current knowledge gaps. Finally, we discuss the potential of foxtail millet as a C4 model species and outline future perspectives of C4 plant microbiome research. [ABSTRACT FROM AUTHOR]

Rotational benefit of pea (Pisum sativum L.) may reduce N fertilization rate and sustain malt barley (Hordeum vulgare L.) yield and quality in the malt barley‐pea rotation. This study examined the effect of cover crop [oat (Avena sativa L.) cover crop vs. none] and N fertilization rate (0, 40, 50, 60, 70, and 80 kg N ha−1) on malt barley growth, yield, and quality in the malt barley‐pea rotation from 2012 to 2019 in the northern Great Plains. Cover crop biomass yield and N accumulation were greater in 2016 than other years. Compared to fallow, malt barley plant density with cover crop was 9%–13% lower from 2013 to 2015, but 10% greater in 2017. Malt barley straw yield was 38% greater in 2017 and grain yield 15%–39% greater in 2017 and 2018, but grain plumpness was 5%–10% lower in 2014 and 2017 with than without cover crop. Increasing N fertilization rate linearly increased grain yield and N uptake, but reduced grain test weight and plumpness in most years. Straw N concentration and uptake and grain protein concentration varied by year. Because of the similar grain yield, protein concentration, plumpness, and test weight between 60 and 80 kg N ha−1, 60 kg N ha−1 can be recommended to sustain malt barley yield and quality in the malt barley‐pea rotation, regardless of cover crops. This helps to reduce N fertilization rate by 20 kg N ha−1 for malt barley in dryland cropping systems of the US northern Great Plains. Core Ideas: Malt barley growth, yield, and quality in response to cover cropping and N fertilization were examined in malt barley‐pea rotation.Malt barley straw and grain yields were lower, but grain plumpness was greater with than without cover cropping.Increasing N fertilization rate increased grain yield and N uptake but reduced grain test weight and plumpness.A 60 kg N ha−1 of N fertilization rate can be used to sustain mall barley yield and quality in the malt barley‐pea rotation.This resulted in a reduction of 20 kg N ha−1 of N fertilization rate from the recommended rate of 80 kg N ha−1. [ABSTRACT FROM AUTHOR]

Introducing integrated crop‐livestock systems into row crop production promotes income diversification and potential soil health benefits through cover crop grazing on degraded soils of the southeastern United States, but effects of these practices on crop yields and soil health in Coastal Plain soils are not well established. A 4‐year study was performed to evaluate the effects of grazing a multi‐species winter cover crop on soil health and crop yields under mid‐February, mid‐March, and mid‐April cattle removal dates and a non‐grazed control within an annual cotton (Gossypium hirsutum L.) and peanut crop rotation (Arachis hypogaea L.). Chemical soil health indicators (soil organic carbon and permanganate oxidizable carbon), physical soil health indicators (water‐stable aggregates and penetration resistance), biological soil health indicators (microbial biomass carbon, soil respiration, and arbuscular mycorrhizal fungi colonization), crop yield, and cover crop biomass were evaluated. Cover crop biomass at termination was reduced by 3660, 5250, and 5610 kg ha−1 for the mid‐February, mid‐March, and mid‐April cattle removal treatments compared to the non‐grazed control. No grazing treatment effects were observed for biological soil properties. Soil organic carbon was higher in the non‐grazed treatment than the mid‐April grazing treatment across 0‐ to 30‐cm depth. Penetration resistance across 0‐ to 50‐cm depth and water‐stable aggregates at the 0‐ to 30‐cm depth were both negatively impacted by increased grazing period lengths. Results from this study suggest that longer cover crop grazing periods have little effect on biological and chemical soil health indicators in the short term but can negatively impact some physical soil health indicators. Core Ideas: Grazing cover crops has minimal effects on biological soil health indicators.Longer grazing periods can have more negative effects on soil physical health indicators.Improvements in soil organic carbon levels were highest in the non‐grazed treatment. [ABSTRACT FROM AUTHOR]

Plant cover and biochemical composition are essential parameters for evaluating cover crop management. Destructive sampling or estimates with aerial imagery require substantial labor, time, expertise, or instrumentation cost. Using low‐cost consumer and mobile phone cameras to estimate plant canopy coverage and biochemical composition could broaden the use of high‐throughput technologies in research and crop management. Here, we estimated canopy development, tissue nitrogen, and biomass of medium red clover (Trifolium pratense L.), a perennial forage legume and common cover crop, using red‐green‐blue (RGB) indices collected with standard settings in non‐standardized field conditions. Pixels were classified as plant or background using combinations of four RGB indices with both unsupervised machine learning and preset thresholds. The excess green minus red (ExGR) index with a preset threshold of zero was the best index and threshold combination. It correctly identified pixels as plant or background 86.25% of the time. This combination also provided accurate estimates of crop growth and quality: Canopy coverage correlated with red clover biomass (R2 = 0.554, root mean square error [RMSE] = 219.29 kg ha−1), and ExGR index values of vegetation pixels were highly correlated with clover nitrogen content (R2 = 0.573, RMSE = 3.5 g kg−1) and carbon:nitrogen ratio (R2 = 0.574, RMSE = 1.29 g g−1). Data collection were simple to implement and stable across imaging conditions. Pending testing across different sensors, sites, and crop species, this method contributes to a growing and open set of decision support tools for agricultural research and management. Core Ideas: Cover crop managemet has a need for robust sensing methods using low‐cost, readily available indices.Multiple red‐green‐blue (RGB) indices were compared to track the growth and nitrogen concentration of a forage cover crop.The top‐performing index (ExGR) correlated with cover crop biomass, N content, and carbon:nitrogen ratio (R2 > 0.55).These results are useful for cover crop management if embedded in regional systems for annual sampling of biomass and model parameterization. [ABSTRACT FROM AUTHOR]

The New York State (NYS) Climate Act aims for net-zero emissions across all economic sectors by 2050, with renewable biofuels playing a key role in this transition. Approximately half of the biomass required for these biofuels is expected to come from purpose-grown sources like willow. To address this demand, we assessed land availability and biomass production potential for willow using a GIS-based fuzzy logic Land Suitability Assessment (LSA) model under three land scenarios: (1) including all cropland, (2) excluding conventional crops, and (3) excluding any cropland. Our findings show that NYS has the potential for between 1.07 and 1.59 million ha for willow cultivation, capable of producing 14.0 to 20.6 million dry Mg of biomass annually. Grassland/pasture accounts for 32–51%, and herbaceous cover for 32–48% of the potential areas. Between 33% and 53% of the area identified was in parcels that were 2–20 ha in size. These results highlight the considerable potential for purpose-grown biomass in NYS, supporting the state's decarbonization goals and renewable energy transition. [ABSTRACT FROM AUTHOR]

Conventional mineral fertilization (CMF) is a common practice in infertile sugarcane-cultivated tropical soils, increasing production costs and environmental concerns. Combining CMF with composted sewage sludge (CSS) could be a sustainable strategy. We aim to evaluate changes in soil chemical properties, macro- and micronutrient concentrations in the soil surface (Ap1; 0–25 cm) and subsurface (Ap2; 25–50 cm) horizons, after CSS application with or without CMF in sugarcane cultivation (first and second ratoon cane). Eleven treatments, featured by CSS increase rates and mixed with CMF at different concentrations, were tested in the first ratoon; during the second, the CSS residual effect was evaluated. Applying CSS in sugarcane-cultivated soils, improved the following: (i) soil organic matter, pH, the sum of bases, cation-exchange capacity, and base saturation; (ii) overall nutrient concentrations (P, K, Ca, Mg, B, Cu, and Zn). The treatments showing the best performances were those with 5.0 Mg ha−1 of CSS. Composted sewage sludge has the potential for use as an organic natural fertilizer reducing the need for CMF. When applied in infertile tropical soils, additional positive effects can be achieved, such as decreasing production costs and providing socio-economic benefits. [ABSTRACT FROM AUTHOR]

Forest and biomass crops for bioenergy and bioproducts can promote a sustainable bioeconomy while effectively reducing greenhouse gas (GHG) emissions to mitigate global warming. One of the most concerning issues is selecting and using appropriate modeling and analytical technologies to optimize the benefits of multi-feedstock biomass supply chains, including logistics. Machine learning (ML) has been used to solve increasingly complex supply chain problems, providing powerful tools for sustainable forest management and biomass resource development. Existing research is extensive and spans many different ML techniques, but synthesis is needed to help guide the adoption of these rapidly evolving tools. This review summarizes ML applications in forest and biomass supply chain management in terms of data, algorithms, and process examples, with an emphasis on direct application to supply chain management. ML is a viable technique to support strategic, operational, and tactical planning and decision-making in this field and can enhance the environmental and economic performance of diverse forest and biomass supply chains. [ABSTRACT FROM AUTHOR]

This study reveals patterns of yield and survival of short-rotation coppice (SRC) willow cultivars over eight rotations (1993–2019). Cultivars fell into four broad categories: commercial, released, stable, and decline. SV1, the singular cultivar that advanced to commercial deployments, had first-rotation yields of 8.9 Mg ha−1 a−1, peaking at 15.2 Mg ha−1 a−1 by the fourth. Mean yields from rotations 2–8 were still 36% above first-rotation yields, confirming the commercial potential for this cultivar over 26 years. The released group (four cultivars) had stable yields over six rotations (approximately 3 to 7 Mg ha−1 a−1), rising to match commercial yields (10 Mg ha−1 a−1) between the sixth and eighth rotation. Most of the cultivars were in the stable group that had relatively consistent yields over time. First-rotation yields in this group were approximately 5 Mg ha−1 a−1, and average yield increased by 23% for rotations 2–8. The two cultivars in the decline group were impacted by disease and browsing that lowered survival and growth. These findings are crucial for understanding willow systems' potential over their full lifespan as a bioenergy crop, which is a crucial input into yield, economic, and environmental models. [ABSTRACT FROM AUTHOR]

The article is devoted to the study of problematic issues of legal support of agro-energy relations under martial law and elaboration of proposals for improving the mechanism of their legal regulation. The author emphasizes the need to preserve and realize the powerful agricultural potential of Ukraine and to counteract the threats and losses of martial law, in particular in the energy sector, and to counteract climate change, which, in turn, makes it expedient to study the legal nature, content, problems and novelties of legal support for agro-energy relations. The author identifies the following features of agro-energy relations: an independent type of agrarian legal relations; a complex agrarian legal category covering a wide range of relations: production relations for growing energy crops and carrying out other types of agricultural activities which result in biomass production; relations for its processing into biofuels and their sale; biotechnological relations for ensuring wastefree agricultural production; research relations in the field of alternative energy; agro-protective relations in the field of stimulating biofuel production; regulatory relations; agro-ecological relations, etc. It is emphasized that these relations are of a regulatory nature; aimed at ensuring the effective development of the main branches of agricultural production; characterized by a special subject composition, public-private nature of their regulation, dynamism due to permanent legislative changes, etc. The author emphasizes the need for comprehensive and effective special regulation of agro-energy relations. The article examines the current state of legal support for agro-energy relations, analyzes novelties and identifies the problems of their legislative regulation. It is proved that improvement of legislation in the field of agroenergy relations will contribute to preservation and realization of the potential of the agrosphere, overcoming energy dependence and ensuring national security of our country, sustainable socio-economic development, combating climate change, integration into the European space, proper functioning of agribusiness and sustainable development of the agrosphere. [ABSTRACT FROM AUTHOR]

The aboveground biomass (AGB) of summer maize is an important indicator for assessing crop growth status and predicting yield, playing a significant role in agricultural management and decision-making. Traditional on-site measurements of AGB are limited, due to low efficiency and a lack of spatial information. The development of unmanned aerial vehicle (UAV) technology in agriculture offers a rapid and cost-effective method for obtaining crop growth information, but currently, the prediction accuracy of summer maize AGB based on UAVs is limited. This study focuses on the entire growth period of summer maize. Multispectral images of six key growth stages of maize were captured using a DJI Phantom 4 Pro, and color indices and elevation data (DEM) were extracted from these growth stage images. Combining measured data such as summer maize AGB and plant height, which were collected on the ground, and based on the three machine learning algorithms of partial least squares regression (PLSR), random forest (RF), and long short-term memory (LSTM), an input feature analysis of PH was carried out, and a prediction model of summer maize AGB was constructed. The results show that: (1) using unmanned aerial vehicle spectral data (CIS) alone to predict the biomass of summer maize has relatively poor prediction accuracy. Among the three models, the LSTM (CIS) model has the best simulation effect, with a coefficient of determination (R2) ranging from 0.516 to 0.649. The R2 of the RF (CIS) model is 0.446–0.537. The R2 of the PLSR (CIS) model is 0.323–0.401. (2) After adding plant height (PH) data, the accuracy and stability of model prediction significantly improved. R2 increased by about 25%, and both RMSE and NRSME decreased by about 20%. Among the three prediction models, the LSTM (PH + CIS) model had the best performance, with R2 = 0.744, root mean square error (RSME) = 4.833 g, and normalized root mean square error (NRSME) = 0.107. Compared to using only color indices (CIS) as the model input, adding plant height (PH) significantly enhances the prediction effect of AGB (aboveground biomass) prediction in key growth periods of summer maize. This method can serve as a reference for the precise monitoring of crop biomass status through remote sensing with unmanned aerial vehicles. [ABSTRACT FROM AUTHOR]

Aboveground biomass (AGB) is a critical indicator for monitoring the crop growth status and predicting yields. UAV remote sensing technology offers an efficient and non-destructive method for collecting crop information in small-scale agricultural fields. High-resolution hyperspectral images provide abundant spectral-textural information, but whether they can enhance the accuracy of crop biomass estimations remains subject to further investigation. This study evaluates the predictability of winter canola AGB by integrating the narrowband spectra and texture features from UAV hyperspectral images. Specifically, narrowband spectra and vegetation indices were extracted from the hyperspectral images. The Gray Level Co-occurrence Matrix (GLCM) method was employed to compute texture indices. Correlation analysis and autocorrelation analysis were utilized to determine the final spectral feature scheme, texture feature scheme, and spectral-texture feature scheme. Subsequently, machine learning algorithms were applied to develop estimation models for winter canola biomass. The results indicate: (1) For spectra features, narrow-bands at 450~510 nm, 680~738 nm, 910~940 nm wavelength, as well as vegetation indices containing red-edge narrow-bands, showed outstanding performance with correlation coefficients ranging from 0.49 to 0.65; For texture features, narrow-band texture parameters CON, DIS, ENT, ASM, and vegetation index texture parameter COR demonstrated significant performance, with correlation coefficients between 0.65 and 0.72; (2) The Adaboost model using the spectra-texture feature scheme exhibited the best performance in estimating winter canola biomass (R2 = 0.91; RMSE = 1710.79 kg/ha; NRMSE = 19.88%); (3) The combined use of narrowband spectra and texture feature significantly improved the estimation accuracy of winter canola biomass. Compared to the spectra feature scheme, the model's R2 increased by 11.2%, RMSE decreased by 29%, and NRMSE reduced by 17%. These findings provide a reference for studies on UAV hyperspectral remote sensing monitoring of crop growth status. [ABSTRACT FROM AUTHOR]