Although there are many new types of environmentally friendly fertilizers that can improve maize yield, chemical fertilizers are the most widespread type of fertilizer used in the agricultural sector of China due to their low cost and ease of application. However, the misuse of chemical fertilizers could lead to environmental problems, such as the massive emission of greenhouse gases (GHG). Therefore, it is important to determine how fertilizer-use efficiency (FUE) could be improved to stabilize or increase maize yield while reducing GHG emissions. In this study, we collected 6618 date records which include three datasets (for N, P, and K) from five maize-growing regions in China from 2005 to 2018, and performed a meta-analysis on the effects of N, K, and P fertilization levels on maize yield, partial factor productivity (PFP), agronomic efficiency (AE), and the carbon footprint of maize production. Additionally, scenario analyses were performed to estimate optimal fertilizer application rates for stabilizing or increasing maize yield while reducing GHG emissions. It was shown that FUE and maize yield responses to fertilization level varied in different regions. Compared to the past, the maize production of China has improved significantly in terms of FUE and its carbon footprint in recent years. Because of improvements in maize cultivars and cultivation technologies, it is possible to decrease N, P, and K application rates and reduce per unit area carbon footprint of maize, without compromising yield. In the future, N fertilization should be reduced by 10% from current levels, and the application of P and K fertilizers should be increased or decreased depending on the conditions of each maize-growing region. Thus, it should be possible to stabilize or even increase yields and reduce GHG emissions of maize production, thereby achieving green and efficient development. Full article

Optimising fertilisation is an important part of maximising vegetable yield and quality whilst minimising environmental hazards. An accurate and efficient scheme of irrigation and fertiliser based on plants’ nutrient requirements at different growth stages is essential for the effective intensive production of greenhouse pepper (Capsicum annuum L.). In this study, the effects of reducing fertilisation rate by 20%, 40%, 60% and 80% from the day 6 to day 0 before harvest for each layer of peppers on growth, yield, quality and nutrient utilisation were evaluated. The results showed that the morphological indicators (plant height and stem diameter) and biomass of plants decreased gradually with the increase in fertiliser reduction rate. Compared with control (CK) plants, the 20–40% reduction in fertiliser application rate did not cause a significant decrease in biomass and stem diameter but significantly increased the accumulation of N (13.52–15.73%), P (23.09% in 20% reducted-treatment) and K (13.22–14.21%) elements in plants. The 20–80% reduction in fertiliser application before harvest had no significant effects on the nutrient agronomic efficiency of N, P and K elements. However, it decreased the physiological nutrient efficiency and significantly improved the nutrient harvest index of N, P and K. Appropriate reduction in fertiliser application significantly increased the nutrient recovery efficiency (20–40% reduction) and nutrient partial-factor productivity (40% reduction) of N (3.35–6.00% and 12.87%), P (2.47–2.92% and 14.01%) and K (7.49–15.68% and 14.01%), respectively. Furthermore, reducing the fertilisation rate by 20–40% before each harvest had a certain positive effect on the C and N metabolism of pepper leaves and fruits. In particular, the activities of N metabolism-related enzymes (nitrate reductase, nitrite reductase, glutamine synthase, glutamate synthase and glutamate dehydrogenase) and C metabolism-related enzymes (sucrose phosphate synthase, sucrose synthetase, acid invertase and neutral invertase) in leaves and fruits did not significantly different or significantly increased compared with those in CK plants. The results of the representative aromatic substance contents in the fruit screened by the random forest model showed that compared with the CK plants, reducing the fertiliser application by 20–40% before harvest significantly increased the content of capsaicin and main flavour substances in the fruit on the basis of stable yield. In summary, in the process of pepper substrate cultivation, reducing the application of nutrients by 40% from the day 6 to day 0 before each harvest could result in stable yield and quality improvement of the pepper. These results have important implications for institutional precision fertilisation programs and the improvement of the agroecological environment. Full article

Potted-seedling machine transplantation (PSMT) is an innovative method of mechanical rice transplanting to improve seedling quality and reduce mechanical injury relative to blanket-seedling machine transplantation (BSMT). However, the responses of yield, grain quality, and risk of lodging in rice to PSMT have not yet been comprehensively defined. Here, we present a meta-analysis of 67 peer-reviewed studies with 382 field observations to investigate the impacts of PSMT on rice yield, grain quality, and lodging resistance in mainland China. The results indicated that compared to BSMT, PSMT increased grain yield, aboveground biomass, and nitrogen uptake by an average of 8.4%, 6.2%, and 7.2%, respectively. PSMT boosted grain yield with hybrid rice (+10.2%) more strongly than with inbred rice (+6.9%). PSMT improved the brown rice rate (+0.74%), milled rice rate (+1.1%), head rice rate (+2.3%), and gel consistency (+4.4%) while reducing the amylose content by 3.7% with no significant effects on the chalky grain rate, chalkiness, length/width ratio, or protein content. The increase in the milled rice rate under PSMT was greater with hybrid rice than with inbred rice. PSMT reduced the lodging index at the first (−5.1%), second (−9.4%), and third (−8.0%) internodes. In conclusion, PSMT is a promising practice for simultaneously improving rice yield, milling quality, cooking and eating quality, and lodging resistance in paddies. In addition, the grain yield and milling quality of hybrid rice under PSMT are higher than those of inbred rice. Full article

Cover crops (CC) promote soil health, but the termination method can condition the benefits for soil microorganisms. In a greenhouse experiment, we evaluated the legacy effects of four common CC termination methods on mycorrhization, soil microbial abundance, structure, and activity, as well as other soil properties, and its interaction with water levels (well-watered and water deficit). Mowing and residue incorporation (INC), glyphosate (GLY), roller crimper (ROL) and glyphosate + roller crimper (RGL) were evaluated, together with no CC, at two sampling dates of a subsequent maize. The water level modulated the soil microbial response to CC termination methods, especially in the glyphosate methods. Legacy effects on soil microbial attributes were notable and evolved differently from maize, from pre-emergence to ~3 months later. At final sampling, INC showed the best microbial response at both water levels, enhancing most microbial attributes. ROL was the second most beneficial method, especially in well-watered soil, promoting fungi but nullifying the CC positive effect on bacteria. Regardless of water level, GLY and RGL showed a similar microbial response. In well-watered soil, GLY and RGL had a negative effect on the total fungi, which separated the RGL response from the ROL. Overall, the time since CC termination and water level modulated the soil microbial response to the termination methods. Further research is needed to investigate CC termination impacts under different environmental conditions, in order to better understand the processes involved and provide farm-level recommendations. Full article

Allelopathy is a physiological process with an ecological concept and application. Allelopathy is the result of the production of biologically active molecules by growing plants or their remains, which may have a direct effect on the growth and development of individuals of the same species or other species after changing their shape and entering the environment. As regards, the use of natural compounds in the control of weeds and pests is a priority. In this research, the allelopathic activity of 123 specimens of medicinal and aromatic plants were investigated individually by the dish-pack method using lettuce seeds as a model. Then, the strongest inhibitory ones were selected and their allelopathic interaction effects were investigated for the first time by interacting them together. Two methods were used to evaluate allelopathic interaction effects: calculating Fractional Inhibitory Concentration (FIC) and drawing Isobologram diagrams. Lettuce hypocotyl length, root length, germination percentage, and germination rate were investigated. Pelargonium graveolens (leaf) had the greatest inhibitory effect on lettuce radicle growth (EC₅₀ = 5.31 mg/well) and Echinophora platyloba (stem) had the greatest effect on hypocotyl growth inhibition (EC₅₀ = 7.91 mg/well). Also, the lowest lettuce germination percentages were observed in the treatments Lavandula officinalis (flower) and Nepeta binaloudensis (leaf), respectively (23.61, 22.85%). The highest inhibitory effect by considering lettuce germination rate was detected in Salvia ceratophylla (leaf), (12.86 seed/day) and the lowest belonged to Nepeta binaloudensis (leaf) and Lavandula officinalis (flower), respectively (3.60, 3.32 seed/day). According to FIC calculations and isobolograms, two types of interaction, including synergist (Nepeta binaloudensis (leaf) with Trachyspermum ammi (fruit) and Nepeta binaloudensis (leaf) with Lavandula officinalis (flower) and antagonist (Pelargonium graveolens (leaf) with Lavandula officinalis (flower)), were observed significantly among the plants tested in this research. These interactions can be used to prepare more effective natural herbicides and decrease the use of herbicides. Full article

Mungbean (Vigna radiata L. Wilczek) is an important short-duration grain legume of the genus Vigna that has wider adaptability across agro-climatic regions and soil types. Significant strides have been made towards the development of superior, high-yielding, and climate resilient cultivars in mungbean. A number of donors for various traits to have been deployed in introgression breeding. However, the use of common sources of resistance to different biotic stresses may lead to boom and bust cycles due to the appearance of new races or biotypes. Therefore, broadening the genetic base using wild and exotic plant genetic resources may offer a better quality of durable resistance. Many crop wild relatives (CWRs) confer a high degree of resistance against multiple diseases. Recently, several agronomically important genes have been mapped using inter-specific populations, which are being deployed for the improvement of mungbean. In such a situation, tagging, mapping, and exploiting genes of interest from cross-species donors for stress tolerance will offer novel genetic variations. This will also provide increased opportunities for the selection of desirable types. Advances in genomics and transcriptomics have further made it easy to tag the cross-compatible resistance loci and study their expression for delineating the mechanism of resistance. The comparative analysis of omics technology also helps in understanding the evolution and offers a scope for using cross-specific target genes for mungbean improvement. This review focuses on the effective utilization of cross-species cultivated and wild relatives as well as their omics resources for breeding multiple disease-resistant mungbean cultivars. Full article

Soil contamination with trace elements (TEs) is a pressing problem limiting the cultivation of agricultural crops; however, the non-food energy crop Miscanthus × giganteus (M×g) can be grown on such soil. The effect of a new plant growth regulator (PGR), Kamethur, and conventional Charkor was studied when M×g was cultivated in TE-contaminated soils from Všebořice and Chomutov, in the Northern Czech Republic. Kamethur was beneficial for achieving a higher leaves and stem biomass (by 57.1 and 126%, respectively) in the more contaminated Všebořice soil, while Charkor increased only the leaves biomass (49.5%). Analysis of the comprehensive bio-concentration index showed that Charkor decreased stem accumulation of elements essential for plant development (EEs), as well as the potentially toxic (PTEs) elements, by 33.3 and 11.4%, respectively. Kamethur decreased stem accumulation of EEs by 11.4% and increased the accumulation of PTEs by 23.3%. Statistical evaluation of the current results and literature data illustrated the ability of Charkor to reduce the uptake of PTEs, which is critical for converting clean biomass to bioproducts. Further research should confirm the influence of PGRs on the bioparameters and phytoremediation processes of M×g at the field plantation level. Full article

Asia Minor bluegrass (Polypogon fugax Nees ex Steud.) is a problematic grass weed of winter crops in China, where some populations have become resistant to herbicides. Previously, we identified a P. fugax population QS exhibiting target-site-based resistance (TSR) and non-target-site-based resistance (NTSR) to clodinafop-propargyl. This study aims to understand the metabolic resistance to clodinafop-propargyl between susceptible (XC) and resistant (QS) populations of P. fugax in the seedling and tillering stage, separately. Several differentially expressed candidate genes in the seedling and tillering stages were identified by RNA-Seq, including three P450 family genes, one glutathione S-transferase (GST) gene, and two ATP-binding cassette transporters. Additionally, we discovered a GST gene that was significantly differentially expressed in the resistant population during the seedling stage, as well as three peroxidase genes that were presumed to be related to NTSR metabolism. Three other peroxidase genes and one esterase were presumed to be related to NTSR metabolism during the tillering stage of the resistant population. Overexpression of the three randomly selected candidate genes can enhance herbicide-resistance in Arabidopsis transgenic plants. This study provided a novel insight into herbicide metabolism regulation genes during the different growth stages of resistant P. fugax population. Full article

Fluopsin C (FlpC) is an organocupric secondary metabolite with low-molecular-weight, produced by some Pseudomonas and Streptomyces bacteria. The compound was identified in 1970 as prismatic dark-green crystals, with strong antimicrobial activity against several human and phytopathogens. Due to its high cytotoxicity, research on this compound decreased after the 1970s. During the early 2000s, FlpC gained more attention as a promising compound by which to develop new antimicrobials to control human, animal, and plant pathogens. This study provides an overview of the results pertaining to the in vitro and in vivo antimicrobial activity of pure FlpC, as well as semi-purified fractions containing FlpC, against phytopathogenic microorganisms. Furthermore, the bioprospection history of the extensively researched FlpC-producing Pseudomonas aeruginosa LV strain and the related molecular evidence regarding the compound’s biosynthesis are discussed. Overall, FlpC is proposed to be an important alternative to antimicrobial resistance in human and animal health, and in tackling the negative environmental impacts caused by the exacerbated use of pesticides against phytopathogens. Full article

Agricultural and livestock wastes are an important resource for the production of renewable fuels such as biomethane, and the effective management of the components of supply chain, such as available biomass feedstock, are critical to the transition to a low-carbon circular economy. Considering that more than half of the emissions (CO₂eq) generated in agriculture come from the use of fossil fuels to power tractors and other agricultural machinery, replacing diesel fuel in tractors with biofuels produced within the agricultural supply chain could contribute to greenhouse gas emissions reduction and to energy self-sufficiency for the local agricultural sectors. This study evaluated, at the regional level (Piedmont—north-west Italy), the potential production of biomethane from local agricultural wastes (crop residues and livestock manure), the potential energy supply to power tractors and the potential CO₂ emission reduction by replacing diesel fuel. Based on mean annual available agricultural wastes over the last seven years (2015–2021) in the Piedmont region, the annual potential biomethane yield of 910 × 10⁶ m³ year⁻¹ was estimated, equivalent to a thermal energy of 30.1 × 10⁹ MJ year⁻¹, which is 3.8 times higher than the energy requirements for the regional tractors’ fleet. The estimated potential CO₂ emission reduction is about 93.8 t of CO₂ year⁻¹, corresponding to 16.8% potential reduction. The study demonstrates the potential of local agriculture to replace diesel fuel with biomethane from waste to meet energy needs and carbon neutrality. Full article

The shortage of water resources makes it urgent to increase agricultural irrigation efficiency. In response to this need, this study develops a real-time adaptive control irrigation (RACI) system for border irrigation. Avoiding the need for traditional real-time control systems to calculate soil infiltration properties in real-time, RACI adjusts the inflow rate based on the difference between the actual and expected advance time. Simulations of the collected data are used to evaluate and analyze the sensitivity of RACI to input parameters, and field experiments were carried out to further verify the irrigation performance and efficiency. The experimental results indicate that RACI delivers an average application efficiency, distribution uniformity, requirement efficiency, and deep percolation of 0.930, 0.884, 0.954, and 0.070, respectively. A sensitivity analysis of irrigation input parameters (infiltration parameter, roughness coefficient, inflow rate, and slope) shows that the irrigation performance of RACI remains satisfactory even when the parameters are varied. Given the satisfactory irrigation performance and robustness and the more facile operation than traditional real-time control systems, RACI has the potential to become widely used. Full article

Leaf photophysiological characteristics are the main indexes that determine crop yield formation. However, it remains unclear whether photosynthesis is systematically regulated via the cropping pattern and nitrogen supply when maize crops are planted with a high density. So, a field experiment that had a three-factor split-plot arrangement of treatments was conducted from 2020 to 2021. The main plot was two cropping patterns that included the sole cropping of maize and wheat–maize intercropping. The split plot had two nitrogen application rates: a traditional nitrogen application rate (N2, 360 kg ha⁻¹) and one reduced by 25% (N1, 270 kg ha⁻¹) for maize. The split–split plot had three planting densities: a traditional density (M1, 78,000 plant ha⁻¹), a medium density (M2, 10,400 plant ha⁻¹), and a high density (M3, 129,000 plant ha⁻¹) for sole maize; the corresponding densities of intercropped maize were 45,000, 60,000, and 75,000 plant ha⁻¹, respectively. The grain yield, the photosynthetic traits, and chlorophyll a fluorescence of the maize were assessed. The results showed that a 25% nitrogen reduction and dense planting had a negative impact on the individual maize’s photosynthesis. However, intercropping could alleviate these drawbacks. When the maize was grown in the intercropping system at a lower nitrogen level and a medium planting density (IN1M2), the photosynthetic traits were better or similar to those of the traditional treatment (SN2M1) at the reproductive growth stage. Moreover, IN1M2 improved the light energy distribution among photochemistry, photo-protective and heat dissipation process of maize compared with SN2M1. A grey relation analysis demonstrated that the Pn and Tr of the individual maize played the most significant role in the group’s productivity. Thus, the IN1M2 treatment achieved the highest grain yield and can be recommended as a feasible agronomic practice in oasis-irrigated regions. Full article

An Aspergillus niger endo-1,4-β-mannanase, Man26A, was confirmed by FTIR and XRD to be immobilised on glutaraldehyde-activated chitosan nanoparticles via covalent bonding. The immobilisation (%) and activity yields (%) were 82.25% and 20.75%, respectively. The biochemical properties (pH, temperature optima, and stability) were then comparatively evaluated for both the free and immobilised Man26A. The optimal activity of Man26A shifted to a lower pH after immobilisation (pH 2.0–3.0, from pH 5 for the free enzyme), with the optimum temperature remaining unchanged (60 °C). The two enzymes exhibited identical thermal stability, maintaining 100% activity for the first 6 h at 55 °C. Substrate-specific kinetic analysis showed that the two enzymes had similar affinities towards locust bean gum (LBG) with varied V_max values. In contrast, they showed various affinities towards soybean meal (SBM) and similar V_max values. The immobilised enzyme was then employed in the enhancement of the functional feed/prebiotic properties of SBM from poultry feed, increasing mannooligosaccharides (MOS) quantities. The SBM main hydrolysis products were mannobiose (M2) and mannose (M1). The SBM-produced sugars could be utilised as a carbon source by probiotic bacteria; Streptococcus thermophilus, Bacillus subtilis, and Lactobacillus bulgaricus. The results indicate that the immobilised enzyme has the potential for use in the sustainable and cost-effective production of prebiotic MOS from agricultural biomass. Full article

With the expansion of cucumber cultivation, many growers continue to experience extreme weather and environmental issues. This study aimed to examine and model the effects of low temperature (LT) and poor light (PL) stresses on cucumber growth. The experiment was designed as an orthogonal experiment that analyzed temperature, light, and duration. The daily maximum/minimum temperatures of the experiment were set as per the following four levels: 13 °C/3 °C, 16 °C/6 °C, 19 °C/9 °C, 22 °C/12 °C, and the control at 28 °C/18 °C. The light was divided into two levels: 200 μmol∙m⁻²∙s⁻¹ and 400 μmol∙m⁻²∙s⁻¹, with 800 μmol∙m⁻²∙s⁻¹ as the control. Treatment duration was set at 2, 5, 8, and 11 days. Stress with different LT, PL, and duration was expressed using the stress effect (0–1), which decreased with an increase in stress level. Meanwhile, treatment with a temperature of 3 °C and light of 400 μmol∙m⁻²∙s⁻¹ for 11 days had the smallest effect on stress, which was only 67% of that of the control following 50 days of recovery, and had the most severe effect on cucumber growth. The proportion of dry weight allocated to leaves and stems decreased with increasing low temperatures and poor light stress, but the proportion allocated to fruit increased. The highest percentage of fruit distribution was found in the treatment with temperature of 9 °C, light of 200μmol∙m⁻²∙s⁻¹, and 11 days duration, being 3.57 times higher than the control. In order to better investigate the effects of LT and PL stress on cucumber growth, light and temperature effect (LTE), growing degree days (GDD), and product of thermal effectiveness and PAR (TEP) models were developed based on temperature and light. The root mean square error (RMSE) of the LTE model was found to be 4.214 g∙plant⁻¹, 36.3% of that of the GDD model and 78.8% of that of the TEP model, better simulating the above-ground dry weight of cucumber plants. Full article

The identification of soybean growth periods is the key to timely take field management measures, which plays an important role in improving yield. In order to realize the discrimination of soybean growth periods under complex environments in the field quickly and accurately, a model for identifying soybean growth periods based on multi-source sensors and improved convolutional neural network was proposed. The AlexNet structure was improved by adjusting the number of fully connected layer 1 and fully connected layer 2 neurons to 1024 and 256. The model was optimized through the hyperparameters combination experiment and the classification experiment of different types of image datasets. The discrimination of soybean emergence (VE), cotyledon (VC), and first node (V1) stages was achieved. The experimental results showed that after improving the fully connected layers, the average classification accuracy of the model was 99.58%, the average loss was 0.0132, and the running time was 0.41 s/step under the optimal combination of hyperparameters. At around 20 iterations, the performances began to converge and were all superior to the baseline model. Field validation trials were conducted applying the model, and the classification accuracy was 90.81% in VE, 91.82% in VC, and 92.56% in V1, with an average classification accuracy of 91.73%, and single image recognition time was about 21.9 ms. It can meet the demand for the identification of soybean growth periods based on smart phone and unmanned aerial vehicle (UAV) remote sensing, and provide technical support for the identification of soybean growth periods with different resolutions from different sensors. Full article