Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.  However, using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.  Thus, we proposed a new approach to approximating irrigations of winter wheat over the North China Plain (NCP), where irrigation occurs extensively during the winter wheat growing season.  This approach used irrigation pattern parameters (IPPs) to define the irrigation frequency and timing.  Then, they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat (PRYM–Wheat), to improve the regional estimates of winter wheat over the NCP.  The IPPs were determined using statistical yield data of reference years (2010–2015) over the NCP.  Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield, with an increase and decrease in the correlation coefficient (R) and root mean square error (RMSE) of 0.15 (about 37%) and 0.90 t ha^–1 (about 41%), respectively.  The data in validation years (2001–2009 and 2016–2019) were used to validate PRYM–Wheat.  In addition, our findings also showed R (RMSE) of 0.80 (0.62 t ha^–1) on a site level, 0.61 (0.91 t ha^–1) for Hebei Province on a county level, 0.73 (0.97 t ha^–1) for Henan Province on a county level, and 0.55 (0.75 t ha^–1) for Shandong Province on a city level.  Overall, PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years, providing a scientific basis for ensuring regional food security.

Climate change has a significant impact on agriculture. However, the impact investigation is currently limited to the analysis of meteorological data, and there is a dearth of long-term monitoring of crop phenology and soil moisture associated with climate change. In this study, temperature and precipitation (1957–2020) were recorded, crop growth (1981–2019) data were collected, and field experiments were conducted at central and eastern Gansu and southern Ningxia, China. The mean temperature increased by 0.36°C, and precipitation decreased by 11.17 mm per decade. The average evapotranspiration (ET) of winter wheat in 39 years from 1981 to 2019 was 362.1 mm, demonstrating a 22.1-mm decrease every 10 years. However, the ET of spring maize was 405.5 mm over 35 years (1985–2019), which did not show a downward trend. Every 10 years, growth periods were shortened by 5.19 and 6.47 d, sowing dates were delayed by 3.56 and 1.68 d, and maturity dates advanced by 1.76 and 5.51 d, respectively, for wheat and maize. A film fully-mulched ridge–furrow (FMRF) system with a rain-harvesting efficiency of 65.7‒92.7% promotes deep rainwater infiltration into the soil. This leads to double the soil moisture in-furrow, increasing the water satisfaction rate by 110‒160%. A 15-year grain yield of maize increased by 19.87% with the FMRF compared with that of half-mulched flat planting. Grain yield and water use efficiency of maize increased by 20.6 and 17.4% when the density grew from 4.5×10⁴ to 6.75×10⁴ plants ha^–1 and improved by 12.0 and 12.7% when the density increased from 6.75×10⁴ to 9.0×10⁴ plants ha^–1, respectively. Moreover, responses of maize yield to density and the corresponding density of the maximum yield varied highly in different rainfall areas. The density parameter suitable for water planting was 174 maize plants ha^–1 with 10 mm rainfall. Therefore, management strategies should focus on adjusting crop planting structure, FMRF water harvesting system, and water-suitable planting to mitigate the adverse effects of climate change and enhance sustainable production of maize in the drylands.

Understanding the spatial distribution of the crop yield gap (YG) is essential for improving crop yields.  Recent studies have typically focused on the site scale, which may lead to considerable uncertainties when scaled to the regional scale.  To mitigate this issue, this study used a process-based and remote sensing driven crop yield model for winter wheat (PRYM-Wheat), which was derived from the boreal ecosystem productivity simulator (BEPS), to simulate the YG of winter wheat in the North China Plain from 2015 to 2019.  Yield validation based on statistical yield data revealed good performance of the PRYM-Wheat Model in simulating winter wheat actual yield (Ya).  The distribution of Ya across the North China Plain showed great heterogeneity, decreasing from southeast to northwest.  The remote sensing-estimated results show that the average YG of the study area was 6 400.6 kg ha^–1.  The YG of Jiangsu Province was the largest, at 7 307.4 kg ha^–1, while the YG of Anhui Province was the smallest, at 5 842.1 kg ha^–1.  An analysis of the responses of YG to environmental factors showed no obvious correlation between YG and precipitation, but there was a weak negative correlation between YG and accumulated temperature.  In addition, the YG was positively correlated with elevation.  In general, studying the specific features of the YG can provide directions for increasing crop yields in the future

The quality of oranges is grounded on their appearance and diameter.  Appearance refers to the skin’s smoothness and surface cleanliness; diameter refers to the transverse diameter size.  They are visual attributes that visual perception technologies can automatically identify.  Nonetheless, the current orange quality assessment needs to address two issues: 1) There are no image datasets for orange quality grading; 2) It is challenging to effectively learn the fine-grained and distinct visual semantics of oranges from diverse angles.  This study collected 12 522 images from 2 087 oranges for multi-grained grading tasks.  In addition, it presented a visual learning graph convolution approach for multi-grained orange quality grading, including a backbone network and a graph convolutional network (GCN).  The backbone network’s object detection, data augmentation, and feature extraction can remove extraneous visual information.  GCN was utilized to learn the topological semantics of orange feature maps.  Finally, evaluation results proved that the recognition accuracy of diameter size, appearance, and fine-grained orange quality were 99.50, 97.27, and 97.99%, respectively, indicating that the proposed approach is superior to others.

This study investigated cold plasmas for multiple biological applications.  Our previous work has found dielectric barrier discharge plasma improves chicken sperm quality.  The number of Sertoli cells (SCs) decides spermatogenesis.  However, whether cold plasma can regulate SC proliferation remains unclear.  This study explored the effects of cold plasma on immature chicken SC proliferation and the regulation mechanism.  Results showed that cold plasma exposure at 2.4 W for 30 s twice with an interval of 6 h produced (P<0.05) the maximum SC viability, cell growth, and cell cycle progression.  SC proliferation-promoting effect of cold plasma treatment was regulated by increasing (P<0.05) the adenosine triphosphate production and the respiratory enzyme activity in the mitochondria.  This process was potentially mediated by the adenosine monophosphate-activated protein kinase (AMPK)–mammalian target of rapamycin (mTOR) signaling pathway, which was regulated by the microRNA (miRNA) targeting regulation directly and by the intracellular reactive oxygen species homeostasis indirectly.  The cold plasma treatment increased (P<0.01) the miR-7450-5p expression and led to a decreased (P<0.01) AMPKα1 level.  On the other hand, miR-100-5p expression was reduced (P<0.05) and led to an increased (P<0.05) mTOR level in SCs.  A single-stranded synthetic miR-7450-5p antagomir and a double-stranded synthetic miR-100-5p agomir reduced (P<0.05) the SC proliferation.  However, this could be ameliorated (P<0.05) by the cold plasma treatment.  Our findings suggest that appropriate cold plasma treatment provides a safe strategy to improve SC proliferation, which is beneficial to elevating male chicken reproductive capacity.

Excessive fertilization has led to nutrient use inefficiency and serious environmental consequences for radish cultivation in North China.  The Nutrient Expert (NE) system is a science-based, site-specific fertilization decision support system, but the updated NE system for radish has rarely been evaluated.  This study aims to validate the feasibility of NE for radish fertilization management from agronomic, economic, and environmental perspectives.  A total of 46 field experiments were conducted over four seasons from April 2018 to November 2019 across the major radish growing regions in North China.  The results indicated that NE significantly reduced N, P₂O₅, and K₂O application rates by 98, 110, and 47 kg ha⁻¹ relative to those in the farmers’ practice (FP), respectively, and reduced N and P₂O₅ inputs by 48 and 44 kg ha⁻¹, respectively, while maintaining the same K₂O rate as soil testing (ST).  Relative to FP and ST, NE significantly increased radish yield by 2.7 and 2.6 t ha⁻¹ (4.2 and 4.0%) and net returns by 837 and 432 USD ha⁻¹, respectively.  On average, NE significantly improved the agronomic efficiency (AE) of N, P, and K (relative to FP and ST) by 42.4 and 31.0, 67.4 kg kg⁻¹ and 50.9, and 20.3 and 12.3 kg kg⁻¹; enhanced the recovery efficiency (RE) of N, P, and K by 11.4 and 7.0, 14.1 and 7.5, and 11.3 and 6.3 percentage points; and increased the partial factor productivity (PFP) of N, P, and K by 162.9 and 96.8, 488.0 and 327.3, and 86.9 and 22.4 kg kg⁻¹, respectively.  Furthermore, NE substantially reduced N and P₂O₅ surpluses by 105.1 and 115.1 kg ha⁻¹, respectively, and decreased apparent N loss by 110.8 kg ha⁻¹ compared to FP.  These results indicated that the NE system is an effective and feasible approach for improving NUE and promoting cleaner radish production in North China.

Flupyradifurone is a promising new insecticide used for controlling Bemisia tabaci during vegetable production.  In this study, we assessed the fitness costs and mode of inheritance associated with resistance to flupyradifurone in B. tabaci by comparing the susceptible strain (MED-S) to one field-evolved flupyradifurone-resistant strain (WH-R, with 199-fold resistance) and one laboratory-selected flupyradifurone-resistant strain (FLU-SEL, with 124-fold resistance).  Progenies of reciprocal crosses between WH-R and MED-S (F_1A, F_1B, and pooled F₁), and between FLU-SEL and MED-S (F_1C, F_1D, and pooled F₁’), showed varying degrees of dominance, indicating that resistance to flupyradifurone in WH-R was autosomal and incompletely dominant, yet in FLU-SEL it was autosomal and incompletely recessive.  Furthermore, the development of resistance to flupyradifurone occurred at the expense of fitness costs for the resistant populations.  Compared to the MED-S strain, WH-R showed a relative fitness of 0.50 with significantly prolonged developmental durations and reduced survival rates of the nymphal and pseudopupal stages, as well as decreased fecundity and hatchability.  Similarly, FLU-SEL showed a relative fitness of 0.65 and also demonstrated prolonged developmental durations and reduced survival rates of nymphs and pseudopupae, as well as decreased hatchability in comparison with the MED-S strain.  However, no significant differences in fecundity were observed between MED-S and FLU-SEL.  The present study provides useful knowledge for formulating pest management strategies in the field, which will allow growers to slow the development of resistance to flupyradifurone and to sustainably control B. tabaci.

microRNAs (miRNAs) and small interfering RNAs (siRNAs) are small non-coding RNAs (ncRNAs) that trigger RNA interference (RNAi) in eukaryotic organisms.  The biogenesis pathways for these ncRNAs are well established in Drosophila melanogaster, Aedes aegypti, Bombyx mori and other insects, but lacking in hymenopteran species, particularly in parasitoid wasps.  Pteromalus puparum is a parasitoid of pupal butterflies.  This study identified and analyzed two pathways by interrogating the P. puparum genome.  All core genes of the two pathways are present in the genome as a single copy, except for two genes in the siRNA pathway, R2D2 (two copies) and Argonaute-2 (three).  Conserved domain analyses showed the protein structures in P. puparum were similar to cognate proteins in other insect species.  Phylogenetic analyses of hymenopteran Dicer and Argonaute genes suggested that the siRNA pathway-related genes evolved faster than those in the miRNA pathway.  The study found a decelerated evolution rate of P. puparum Dicer-2 with respect to Dicer-1, which was contrary to other hymenopterans.  Expression analyses revealed high mRNA levels for all miRNA pathway genes in P. puparum adults and the siRNA related genes were expressed in different patterns.  The findings add valuable new knowledge of the miRNA and siRNA pathways and their regulatory actions in parasitoid wasps.

No tillage (NT) and straw return (S) collectively affect soil organic carbon (SOC).  However, changes in the organic carbon pool have been under-investigated.  Here, we assessed the quantity and quality of SOC after 11 years of tillage and straw return on the North China Plain.  Concentrations of SOC and its labile fractions (particulate organic carbon (POC), potassium permanganate-oxidizable organic carbon (POXC), microbial biomass carbon (MBC) and dissolved organic carbon (DOC)), components of DOC by fluorescence spectroscopy combined with parallel factor analysis (PARAFAC) and the chemical composition of SOC by ¹³C NMR spectroscopy were explored.  Treatments comprised conventional tillage (CT) and NT under no straw return (S0), return of wheat straw only (S1) or return of both wheat straw and maize residue (S2).  Straw return significantly increased the concentrations and stocks of SOC at 0-20 cm depth but no tillage stratified them with enrichment at 0-10 cm and a decrease at 10-20 cm in comparison to CT, especially under S2.  Labile C fractions showed similar patterns of variation to that of SOC, with POC and POXC more sensitive to straw return and the former more sensitive to tillage.  Six fluorescence components of DOC were identified comprising mostly humic-like substances with smaller amounts of fulvic acid-like substances and tryptophan. Straw return significantly decreased the fluorescence index (FI) and autochthonous index (BIX) and increased the humification index (HIX).  No tillage generally increased HIX in topsoil but decreased it and increased the FI and BIX below the topsoil.  The chemical composition of SOC was: O-alkyl C>alkyl-C>aromatic-C>carbonyl-C.  Overall, NT under S2 effectively increased SOC and its labile C forms and DOC humification in topsoil and microbially-derived DOC below the topsoil.  Return of both wheat and maize straw was a particularly strong factor for promoting soil organic carbon in the plough layer, and the stratification of SOC under no tillage may confer long-term influence on carbon sequestration.

Plant photosynthesis assimilates CO₂ from the atmosphere, and CO₂ diffusion efficiency is mainly constrained by stomatal and mesophyll resistance.  The stomatal and mesophyll conductance of plants are sensitive to abiotic stress factors, which affect the CO₂ concentrations at carboxylation sites to control photosynthetic rates.  Early studies conducted relevant reviews on the responses of stomatal conductance to the environment and the limitations of mesophyll conductance by internal structure and biochemical factors.  However, reviews on the abiotic stress factors that systematically regulate plant CO₂ diffusion are rare.  Therefore, in this review, the rapid and long-term responses of stomatal and mesophyll conductance to abiotic stress factors (such as light intensity, drought, CO₂ concentration and temperature) and their physiological mechanisms are summarized.  Finally, future research trends are also investigated.

Accurate rice area extraction and yield simulations are important for understanding how national agricultural policies and environmental issues affect regional spatial changes in rice farming. In this study, an improved regional parametric syntheses approach, that is, the rice zoning adaptability criteria and dynamic harvest index (RZAC-DHI), was established, which can effectively simulate the rice cultivation area and yield at the municipal level. The RZAC was used to extract the rice area using Moderate Resolution Imaging Spectroradiometer time-series data and phenological information. The DHI was calculated independently, and then yield was obtained based on the DHI and net primary productivity (NPP). Based on the above results, we analyzed the spatial–temporal patterns of the rice cultivation area and yield in Northeast China (NEC) during 2000–2015. The results revealed that the methods established in this study can effectively support the yearly mapping of the rice area and yield in NEC, the average precisions of which exceed 90 and 80%, respectively. The rice planting areas are mainly located on the Sanjiang, Songnen and Liaohe plains, China, which are distributed along the Songhua and Liaohe rivers. The rice cultivation area and yield in this region increased significantly from 2000 to 2015, with increases of nearly 58 and 90%, respectively. The rice crop area and yield increased the fastest in Heilongjiang Province, China, whereas small changes occurred in Jilin and Liaoning provinces, China. Their gravity centers exhibited evident northward and eastward shifts, with offset distances of 107 and 358 km, respectively. Moreover, Heilongjiang Province has gradually become the new main rice production region. The methodologies used in this study provide a valuable reference for other related studies, and the spatial-temporal variation characteristics of the rice activities have raised new attention as to how these shifts affect national food security and resource allocation.

Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing (RS) approaches limited their applications over broad regions. In this study, a process-based and remote sensing driven crop yield model for maize (PRYM–Maize) was developed to estimate regional maize yield, and it was implemented using eight data-model coupling strategies (DMCSs) over the Northeast China Plain (NECP). Simulations under eight DMCSs were validated against the prefecture-level statistics (2010–2012) reported by National Bureau of Statistics of China, and inter-compared. The 3-year averaged result could give more robust estimate than the yearly simulation for maize yield over space. A 3-year averaged validation showed that prefecture-level estimates by PRYM–Maize under DMCS8, which coupled with the development stage (DVS)-based grain-filling algorithm and RS phenology information and leaf area index (LAI), had higher correlation (R, 0.61) and smaller root mean standard error (RMSE, 1.33 t ha^–1) with the statistics than did PRYM–Maize under other DMCSs. The result also demonstrated that DVS-based grain-filling algorithm worked better for maize yield than did the harvest index (HI)-based method, and both RS phenology information and LAI worked for improving regional maize yield estimate. These results demonstrate that the developed PRYM–Maize under DMCS8 gives reasonable estimates for maize yield and provides scientific basis facilitating the understanding the spatial variations of maize yield over the NECP.

Fruit yield is the most important horticultural trait of tomato.  SlMBP21, a SEPALLATA subclass MADS-box gene has been reported to have functions in regulating pedicel abscission zone identity and development and controlling sepal size in tomato.  However, we generated transgenic tomato plants which overexpress SlMBP21 and found the transformants displayed curly leaves, abnormally shaped flowers with twisted and opened stamens, reduced yield parameters, and small and light seeds.  Our studies on the gain-of-function phenotype and gene expression level showed that its novel aspects played important roles in determining leaf morphology, flower and inflorescence architecture, and seed size, as well as the fruit yield.  Overexpression of SlMBP21 in tomato resulted in curly leaves with fewer leaflets due to the regulation of the critical leaf polarity genes that cause an imbalance between the midvein adaxial–abaxial cell growth.  Defects in the architecture of flowers and inflorescences resulted in reduced fruit set.  Furthermore, we demonstrated that SlMBP21 plays its role through inhibiting the expression of the genes involved in the determination of seed development in tomato and SlMBP21 protein can interact with other MADS-box protein (SlAGL11, TAGL1 and SlMBP3) to control seed size.  Thus, these results suggest that overexpression of SlMBP21 causes multiple types of damage to plant growth and development, especially fruit yield, in tomato.

It is generally known that the culture for mycoplasma is time-consuming and a variety of nutrients are needed in the culture medium.  This brings a lot of difficulties to mycoplasma research and application, including Mycoplasma mycoides subsp. capri (Mmc).  Furthermore, little research on the characteristics of Mmc metabolism has been reported.  In this study, Mmc PG3 strain cultures were investigated for dynamic gene expression.  Culture samples were harvested during logarithmic phase (PG3-1), stationary phase (PG3-2), decline phase (PG3-3) and late decline phase (PG3-4).  Twelve RNA samples (three replicates for each of the four growth stages considered) from these cultures were collected and sequenced.  Paired comparison between consecutive growth phases in the four growth stages showed 45 significant differentially expressed genes (P<0.01) were linked to PG3 metabolism.  The enzymes these genes coded were mainly involved in ATP synthase, pyrimidine metabolism, nicotinate and nicotinamide metabolism, arginine and proline metabolism.  Among these, cytidylate kinase, fructose 1,6-bisphosphate aldolases Class II, nicotinate-nucleotide adenylyltransferase and dihydrolipoamide dehydrogenase play a key role in Mmc metabolism.  These results provide a baseline to build our understanding of the metabolic pathway of Mmc.