Climate change and farmland environmental pollution have put greater pressure on the sustainability of agricultural production. Based on the provincial panel data of mainland China from 1978 to 2018, climate variables such as precipitation, temperature, and sunshine hours are included into the input indicators, and agricultural non-point source pollution and carbon emissions are taken as undesirable outputs, the agricultural production efficiency (APE) under the dual constraints of climate change and the resource environment was estimated by the super slacks-based measure (SBM)-undesirable model. On the basis of the trajectory of the imbalanced spatiotemporal evolution of APE shown by Kernel density estimation and the standard deviational ellipse (SDE)–center of gravity (COG) transfer model, the spatial convergence model was used to test the convergence and differentiation characteristics of APE. Under the dual constraints, APE presents a “bimodal” distribution with a stable increase in fluctuation, but it is still at a generally low level and does not show polarization, among which the APE in the northeast region is the highest. The COG of APE tends to transfer towards the northeast, and the coverage of the SDE is shrinking, so the overall spatial pattern is characterized by a tendency of clustering towards the north in the north-south direction and a tendency of imbalance in the east-west direction. APE has significant spatial convergence, and there is a trend of “latecomer catching-up” in low-efficiency regions. The introduction of spatial correlation accelerates the convergence rate and shortens the convergence period. The convergence rate is the highest in the central and western regions, followed by that in the northeastern region, and the convergence rate is the lowest in the eastern region. In addition, the convergence rate in different time periods has a phase change. The process of improving the quality and efficiency of agricultural production requires enhancing the adaptability of climate change, balancing the carrying capacity of the resource environment, and strengthening inter-regional cooperation and linkage in the field of agriculture.
Colombia is the world’s largest producer of fique fibers (Furcraea bedinghausii), with a net production of 30,000 tons per year. This work proposes to revalue waste from the Colombian fique agroindustry. For this purpose, cellulose nanofibers were obtained from fique and used as reinforcement material to create acrylic superabsorbent hydrogels. Unreinforced acrylic hydrogels (AHR0) and acrylic hydrogels reinforced with fique nanofibers at 3% w/w (AHR3), 5% w/w (AHR5), and 10 % w/w (AHR10) were synthesized using the solution polymerization method. The best hydrogel formulation for agricultural purposes was chosen by comparing their swelling behavior, mechanical properties, and using scanning electron microscopy (SEM). By raising the nanofiber concentration to 3% (AHR3), the best-chosen formulation, the interaction between the nanofibers and the polymer matrix increased, which favored the network stability. However, beyond AHR3, there was a higher viscosity of the reactive system, which caused a reduction in the mobility of the polymer chains, thus disfavoring the swelling capacity. The reinforced hydrogel proposed in this study (AHR3) could represent a contribution to overcoming the problems of land dryness present in Colombia, an issue that will worsen in the coming years due to the climate emergency.
The micropropagation appears to be a valid alternative method for the production of large-scale, phenotypically homogeneous, and disease-free plants, particularly for spring globe artichoke genotypes. Nevertheless, micropropagated plants have some problems during the acclimatization in field environments. The inoculation with arbuscular mycorrhizal fungi appeared to overcome the transplanting stress. Therefore, a comparison was drawn between the field performances of different vegetative propagation techniques (micropropagated/mycorrhized and offshoots cultivation) of early globe artichoke clones over two growing seasons. The micropropagation/mycorrhization appeared to deliver a better field performance in terms of both plant growth and productivity traits as compared with offshoots cultivated. In particular, the micropopagated/mycorrhized plants exhibited the highest vegetative growth values than the offshoots of the cultivated ones, such as the plant height and the main floral stem length. The micropopagated/mycorrhized plants were also more productive, exceeding the head yield of offshoots cultivated ones by about 63%. However, the micropopagated/mycorrhized plants accumulated almost a month late on the first harvest respect to offshoots cultivated ones. Our data also showed that the effects of the new proposed propagation method were genotype- and season-dependent. Accordingly, some plant growth and productivity traits showed significant ‘propagation method × genotype’ and ‘propagation method × growing season’ interaction. This study revealed that the micropropagation, as well as the mycorrhization, could represent an efficient and sustainable cropping system to reintroduce and increase the productivity of autochthons landraces.
Understanding the methods leading to rice yield increase is vital for sustainable agricultural development. Improving the harvest index (HI) is an important way to increase rice yield. To explore the effects of different water and nitrogen management modes on the rice HI in the black soil region of Northeast China, a field experiment was conducted in 2019 (Y1) and 2020 (Y2). Two irrigation methods, conventional flooding irrigation (FI) and controlled irrigation (CI), were established in the experiment, and four nitrogen application levels (0 kg/ha, 85 kg/ha, 110 kg/ha, and 135 kg/ha) were set during the entire growth period, named N0, N1, N2, and N3. The dry matter weight and the rice yield at the maturity stage were determined, and the HI was then calculated. The results showed that different irrigation modes and nitrogen application levels had significant effects on the rice HI. Under different irrigation modes with the same nitrogen application level during the two years, the comparison regular of HI was consistent. In Y1 and Y2, the HI of FN0 was 3.36% and 5.02% higher than that of CN0 (p < 0.05), and the HI of CN1 was 0.31% and 2.43% higher than that of FN1 (p > 0.05). The HI under CI was significantly higher than that under FI under N2 and N3 (p < 0.05), the HI of CN2 was 4.21% and 4.97% higher than that of FN2, and the HI of FN3 was 13.12% and 20.34% higher than that of CN3. In addition, during the two-year experiment, the HI first increased and then decreased with an increase in the nitrogen application rate under FI and CI. Under the FI treatments, the HI of N1 was the highest, and that of N2 was the highest under the CI treatments. A variance analysis showed that the irrigation pattern and nitrogen application level had significant interactions on the rice HI (p < 0.01), and the appropriate water and N management mode could increase rice the HI by 26.89%. The experimental results showed that the HI of the 110 kg/ha nitrogen application rate under CI was the highest, reaching 0.574 and 0.572, respectively, in two years. This study provides a data reference and theoretical support for realizing water savings, nitrogen reduction, and sustainable agricultural development in the black soil region of Northeast China.
The tractor is a vehicle often used in agriculture. It is mainly used to tow other unpowered agricultural machinery for farming, harvesting, and seeding. They consume a lot of fuel with emissions that often contain a large amount of toxic gases, which seriously jeopardize human health and the ecological environment. Therefore, the electrical tractor is bound to become a future trend. The objective of this study is to design and implement a lightweight, energy-saving, and less polluting electric tractor, which meets the requirements of existing smallholder farmers, equipped with unmanned technology and multi-functions to assist labor and to provide the potential for unmanned operation. We reduced the weight of the tractor body structure to 101 kg, and the bending rigidity and torsional rigidity reached 11,579 N/mm and 4923 Nm/deg, respectively. Two 7.5 kW induction motors driven by lithium batteries were applied, which allows at least 3.5 h of working time.
Environmental and land-use changes put severe pressure on wild plant habitats. The present study aims to assess the biodiversity of wild plant habitats and the associated spatiotemporal environmental changes in the coastal region of Dakahlia Governorate following an integrated approach of remote sensing, GIS, and samples analysis. Thirty-seven stands were spatially identified and studied to represent the different habitats of wild plants in the Deltaic Mediterranean coastline region. Physical and chemical characteristics of soil samples were examined, while TWINSPAN classification was used to identify plant communities. Two free Landsat images (TM and OLI) acquired in 1999 and 2019 were processed to assess changes via the production of land use and cover maps (LULC). Moreover, NDSI, NDMI, and NDSI indices were used to identify wild plant habitats. The floristic composition indicated the existence of 57 species, belonging to 51 genera of 20 families. The largest families were Asteraceae, Poaceae, and Chenopodiaceae. The classification of vegetation led to the identification of four groups. Canonical Correspondence Analysis (CCA) revealed that electrical conductivity, cations, organic carbon, porosity, chlorides, and bicarbonates are the most effective soil variables influencing vegetation. The results of the spectral analysis indicated an annual coverage of bare lands (3.56 km2), which is strongly related to the annual increase in vegetation (1.91 km2), water bodies (1.22 km2), and urban areas (0.43 km2). The expansion of urban and agricultural regions subsequently increased water bodies and caused occupancy of bare land, resulting in the development of wild plant habitats, which are mostly represented by the sparse vegetation class as evaluated by NDVI. The increase in mean moisture values (NDMI) from 0.03 in 1999 to 0.15 in 2019 might be explained by the increase in total areas of wild plant habitats throughout the study period (1999–2019). This may improve the adequacy of environments for wild habitats, causing natural plant proliferation.
OTU deubiquitinase 7A (OTUD7A) can suppress inflammation signaling pathways, but it is unclear whether the gene can inhibit inflammation in goose fatty liver. In order to investigate the functions of OTUD7A and identify the genes and pathways subjected to the regulation of OTUD7A in the formation of goose fatty liver, we conducted transcriptomic analysis of cells, which revealed several genes related to inflammation and immunity that were significantly differentially expressed after OTUD7A overexpression. Moreover, the expression of interferon-induced protein with tetratricopeptide repeats 5 (IFIT5), tumor necrosis factor ligand superfamily member 8 (TNFSF8), sterile alpha motif domain-containing protein 9 (SAMD9), radical S-adenosyl methionine domain-containing protein 2 (RSAD2), interferon-induced GTP-binding protein Mx1 (MX1), and interferon-induced guanylate binding protein 1-like (GBP1) was inhibited by OTUD7A overexpression but induced by OTUD7A knockdown with small interfering RNA in goose hepatocytes. Furthermore, the mRNA expression of IFIT5, TNFSF8, SAMD9, RSAD2, MX1, and GBP1 was downregulated, whereas OTUD7A expression was upregulated in goose fatty liver after 12 days of overfeeding. In contrast, the expression patterns of these genes showed nearly the opposite trend after 24 days of overfeeding. Taken together, these findings indicate that OTUD7A regulates the expression of inflammation- and immune-related genes in the development of goose fatty liver.
With the widespread vaccination against COVID-19, people began to resume regional tourism. Outdoor attractions, such as leisure agricultural parks, are particularly attractive because they are well ventilated and can prevent the spread of COVID-19. However, during the COVID-19 pandemic, the considerations around choosing a leisure agricultural park are different from usual, and will be affected by uncertainty. Therefore, this research proposes a fuzzy collaborative intelligence (FCI) approach to help select leisure agricultural parks suitable for traveler groups during the COVID-19 pandemic. The proposed FCI approach combines asymmetrically calibrated fuzzy geometric mean (acFGM), fuzzy weighted intersection (FWI), and fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (fuzzy VIKOR), which is a novel attempt in this field. The effectiveness of the proposed FCI approach has been verified by a case study in Taichung City, Taiwan. The results of the case study showed that during the COVID-19 pandemic, travelers (especially traveler groups) were very willing to go to leisure agricultural parks. In addition, the most important criterion for choosing a suitable leisure agricultural park was the ease of maintaining social distance, while the least important criterion was the distance from a leisure agricultural park. Further, the successful recommendation rate using the proposed methodology was as high as 90%.
The present study focuses on the impact of copper and silver nanoparticles on the chemical composition and physical properties of rapeseeds and rape sprouts. The seeds and sprouts were obtained from winter rape grown in a three-year cultivation (2018–2020) treated with silver (AgNP) and copper (CuNP) nanoparticles. In addition, the effect of the freeze-drying temperature (20; 40; 60 °C) on selected properties of the sprouts was studied. Spraying growing plants with nanoparticles resulted, in most cases, and depending on the year, in a reduction in the mass of seeds (MTS) by 9.5% (single nanoparticles spray ×1 CuNP in 2018), an increase in the fat content (by 8.80% for ×1 CuNP in 2018), a reduction in the protein content (by 12.93% for ×1 CuNP in 2018) and flavonoid content (by up to 58% for ×1 AgNP and CuNP in 2018), as well as increase in the glucosinolates content by 25% (for double nanoparticles spray ×2 AgNP in 2019). For the sprouts obtained from the rapeseeds, in most cases, a decrease in the content of flavonoids was observed (26.68% for ×1 AgNP; 20 °C in 2018), depending on the year of cultivation, the nanoparticles used, and the drying temperature. The obtained results remain inconclusive, which encourages the authors to undertake further research.