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The current cotton (Gossypium hirsutum L.) fallow farming system causes soil degeneration and cotton yield reduction. Cover cropping is commonly associated with improved soil fertility and crop pro...

A field experiment was performed to assess the carbon footprint (CF) of four cropping systems to identify the sustainable cropping system. The four cropping systems were cotton monoculture (CM), wi...

Identifying the ideal plant nature and canopy structure is of great importance for improving photosynthetic production and the potential action of plants. To address this challenge, an investigation was accomplished in 2018 and 2019 at the Institute of Cotton Research (ICR) of the Chinese Academy of Agricultural Science (CAAS), Henan Province, China. Six cotton varieties with diverse maturities and plant canopy structures were used to evaluate the light interception (LI) in cotton, the leaf area index (LAI), the biomass, and the yield throughout the two years of study. The light spatial distribution in the plant canopy was evaluated using a geographic statistical method, following the increasing quantity of radiation intercepted, which was determined using the rules of Simpson. Compared to the cotton plants with a compact structure, varieties with both a loose and tower design captured a comparatively higher amount of light (average 31.3%) and achieved a higher LAI (average 32.4%), eventually achieving a high yield (average 10.1%). Furthermore, the polynomial correlation revealed a positive relationship between the biomass accumulation in the reproductive parts and canopy-accrued light interception (LI), signifying that light interception is critical for the yield development of cotton. Furthermore, when the leaf area index (LAI) was peaked, radiation interception and biomass reached the highest during the boll-forming stage. These findings will provide guidance on the light distribution in cotton cultivars with an ideal plant structure for light capture development, providing an important foundation for researchers to better manage light and canopies.

The photosynthetically active radiation (PAR) of crop canopy is highly related to yield formation, but how it relates to yield and yield distribution is not well understood. The focus of this study was to explore the relationship between light competition under different densities and yield distributions of cotton. The experiment was conducted in 2019 and 2020 at the Cotton Research Institute of the Chinese Academy of Agricultural Sciences in Anyang city, Henan Province, China. A randomized block design was employed, with a total of three repeats. Each repeat had six density treatments: D1: 15,000, D2: 33,000, D3: 51,000, D4: 69,000, D5: 87,000, and D6: 105,000 plants·ha−1. As predicted, the results showed that the canopy light interception, leaf area index, plant height, and biomass of high-density cotton were higher than those of low-density cotton. The aboveground biomass produced by D6 was the highest, and was 12.9, 19.5, 25.4, 46.3, and 69.2% higher in 2019 and 14.3, 19.9, 32.5, 53.7, and 109.9% higher in 2020 than D5, D4, D3, D2, and D1, respectively. Leaf area, plant height, biomass, boll number, and boll weight were significantly correlated with the light interception rate. D5 (87,000 plants·ha−1) had a higher light interception rate and the highest yield. The highest lint yields produced by D5 were 1673.5 and 1375.4 kg·ha−1 in two years, and was 3.2, 4.3, 5.6, 9.7, and 24.7% higher in 2019, and 6.8, 10.6, 13.5, 21.5, and 34.4% higher in 2020 than D6, D4, D3, D2, and D1, respectively. The boll retention of the lower fruit branch under D5 reached 0.51 and 0.57 in two years, respectively. The shedding rate of the upper fruit branch decreased with the increase in cotton density in two years. The boll retention rate and shedding rate in the lower part of cotton plants were most closely related to light interception, with R2 values of 0.91 and 0.96, respectively. Our study shows cotton yield could be improved through higher light interception by optimizing planting density and canopy structure.

Cotton-winter fallow is the major cropping system of cotton in the Yellow River basin of China, which not only leads to a considerable waste of land and natural resources, but also high greenhouse emissions and a loss of reactive nitrogen. Replacing winter bare fallow in cotton production with February orchid as a cover crop is a new cropping system in this area, but its sustainability is still unknown. Therefore, a field experiment was conducted with two cropping systems (cotton-winter fallow and cotton-February orchid) under four nitrogen application rates (0, 112.5, 168.75, and 225 kg N ha−1). Field observations were incorporated into a life cycle assessment to estimate the carbon footprint, nitrogen footprint, net ecosystem economic benefits, and economic benefits. The estimated carbon footprint per unit of sown area was 43.6–76.1% lower in the cotton-February orchid system than in the cotton-winter fallow system, mainly because of the increase in soil organic carbon. The cotton-February orchid system significantly increased the nitrogen footprint per unit of sown area by 6.7–11.5% under different application rates mainly because of the increase in N2O emissions. The nitrogen application rate significantly impacted the carbon and nitrogen footprints. After accounting for changes in the nitrogen and carbon footprints, the cotton-February orchid system with 168.75 kg N ha−1, which resulted in the highest net ecosystem economic benefits and economic benefits, resulted in a 25.0% reduction in nitrogen fertilizer applied and a 9.5% increase in net ecosystem economic benefits compared with the conventional cotton-winter fallow system and nitrogen fertilizer application rate (225.75 kg N ha−1). Thus, adopting an integrated strategy combining February orchid as a cover crop and a reduced nitrogen fertilizer application contributes to improvements in green and sustainable cotton production systems in the Yellow River basin and other regions with similar ecological conditions.

Modification of the cotton canopy results in shade avoidance and competition for light, which shows that density and spatial arrangement of cotton have a great impact on light interception. This experiment was conducted in 2018 and 2019 in the experimental field at the Institute of Cotton Research of Chinese Academy of Agricultural Science in Anyang city, Henan Province, China. Six plant densities of cotton variety SCRC28 were used to assess spatial competition for light in cotton populations during the whole growing period. Light interception data were collected and analyzed according to the spatial grid method and the extension of Simpson&rsquo, s 3/8 rule. The results showed that at the bottom of the canopy, greater light interception was observed at high densities than at low densities, while in the external part of the layer of the canopy in the horizontal direction, low light interception was recorded at low densities. Leaf area, aboveground biomass and plant height were obviously correlated with light interception, and the cotton population with a higher density (8.7 plants m&minus, 2) performed best at the light interception competition, and with the highest yield. The results will provide guidance on light management through the optimization of the structure of the canopy to provide more solar radiation and a significant basis by which to improve the management of light and canopy architecture.

Analyzing the carbon footprint of crop production and proposing low-carbon emission reduction production strategies can help China develop sustainable agriculture under the goal of 'carbon peak and carbon neutrality'. Cotton is an economically important crop in China, but few reports have systematically quantified the carbon footprint of China's cotton production and analyzed its spatiotemporal changes and driving factors. This study used a life cycle approach to analyze the spatiotemporal changes and identify the main components and driving factors of the carbon footprint of cotton production in China between 2004 and 2018 based on statistical data. The results showed that the carbon footprint per unit area of cotton in Northwest China, the Yellow River Basin and the Yangtze River Basin reached 6220.13 kg CO

The number of cotton plants grown per unit area has recently gained attention due to technology expense, high input, and seed cost. Yield consistency across a series of plant populations is an attractive cost-saving option. Field experiments were conducted to compare biomass accumulation, fiber quality, leaf area index, yield and yield components of cotton planted at various densities (D1, 1.5, D2, 3.3, D3, 5.1, D4, 6.9, D5, 8.7, and D6, 10.5 plants m&minus, 2). High planting density (D5) produced 21% and 28% more lint yield as compared to low planting density (D1) during both years, respectively. The highest seed cotton yield (46,662 kg/ha) and lint yield (1763 kg/ha) were produced by high plant density (D5) while the further increase in the plant population (D6) decreased the yield. The increase in yield of D5 was due to more biomass accumulation in reproductive organs as compared to other treatments. The highest average (19.2 VA gm m&minus, 2 d&minus, 1) and maximum (21.8 VM gm m&minus, 1) rates of biomass were accumulated in reproductive structures. High boll load per leaf area and leaf area index were observed in high planting density as compared to low, while high dry matter partitioning was recorded in the lowest planting density as compared to other treatments. Plants with low density had 5% greater fiber length as compared to the highest plant density, while the fiber strength and micronaire value were 10% and 15% greater than the lowest plant density. Conclusively, plant density of 8.7 plants m&minus, 2 is a promising option for enhanced yield, biomass, and uniform fiber quality of cotton.

Introducing cover crops into crop rotation systems is widely practiced to enhance the sustainability of agricultural production, but comprehensive evaluations of farmlands in cover crop-maize rotations on the North China Plain (NCP) from environmental, economic and net ecosystem economic benefits (NEEB) perspectives have rarely been performed. Therefore, a field experiment was conducted to compare economic benefits (EB), greenhouse gas (GHG) emissions, reactive nitrogen (Nr) losses, soil nutrient cycling values (SNV) and NEEB in three farming systems. The farming systems included a conventional wheat-maize (WM) rotation system, a government-promoted monoculture maize (MM) system and an innovative Orychophragmus violaceus (O. violaceus)-maize (OvM) rotation system. The OvM rotation system achieved more EBs from the maize season but lower annual profits than the WM system, with 68.29% lower GHG emissions and 39.33% lower Nr losses. In addition, the highest SNV was achieved in the OvM rotation system, which was 700.18% and 116.97% higher than those in the WM and MM systems, respectively. Furthermore, the NEEB of the OvM rotation system was 61.92% and 29.31% higher than those of the WM and MM systems, respectively. In conclusion, the OvM rotation is recommended as a sustainable and cleaner maize production farming system for the NCP and other regions with similar ecological conditions because it led to lower annual GHG emissions and Nr losses, as well as higher SNV and NEEB than the other farming systems.

Cotton (Gossypium hirsutum L.) yield variability over time is determined by weather and agronomic factors in site-specific soil conditions. Plant density is among the most important agronomic practices in cotton production. However, the relative importance of each factor remains unclear. Here, we addressed plant density effects and the relative importance against weather factors on yield variability over time using a decade-long (2008–2017) field experiment on cotton crops that consisted of a wide range of plant densities from 1.5 to 10.5 plants m–2 in the Yellow River Valley of China. The results showed that a plant density of 3.3 plants m–2 produced stable productivity across periods of contrasting weather conditions. However, the average plant density for maximum yield was 5.9 plants m–2. As such, there was a trade-off between yield potential and yield stability for cotton crops. Moreover, plant density and weather explained 46.4 % and 29.1 %, respectively, of the variation in cotton yield during 2008–2017. Among weather related factors, air temperature during the growing season had stronger independent explanatory power (25.8 %) than did sunshine hours (5.1 %) and annual precipitation (1.3 %). Taken together, our results not only highlight the importance of focusing on yield stability for sustainable agricultural management recommendations but also underline the necessity of considering the primary weather variations for accurately predicting agricultural yield under climate change.

The growth of winter wheat consumes a substantial amounts of water, and precipitation in most years cannot meet the water demand for the normal growth of winter wheat. The unsuitable irrigation strategies waste a large number of water resource, and the low water use efficiency has become the main factor limiting wheat yields. This research explored the effects of different cultivation managements on water consumption characteristics, water utilization efficiency, and grain yields of winter wheat. A field experiment, in which 4 cultivation managements including traditional cultivation management (T1), optimized cultivation management compared with T1 (T2), super high-yield cultivation management (T3) and optimized cultivation management compared with T3 (T4), was conducted during 2008–2010 to measure the above parameters. The results showed that different cultivation managements had significant effects on the total water consumption amounts and water source compositions. Total water consumption amounts in T1 and T3 managements were significantly higher than that in T2 and T4 managements, possibly from irrigation water. T2 and T4 managements remarkably increased the uptake and utilization of soil storage water and precipitation amounts. T3 and T1 managements increased and decreased water consumption in upper (0–40 cm) and lower (60–100 cm) soil layers, respectively, while effectively increased the consumption of storage water in middle and lower soil layers (60–100 cm) and yield water use efficiency (WUEY), precipitation water use efficiency (WUEP), soil water use efficiency (WUES), irrigation water use efficiency (WUEI), and irrigation efficiency (IE) in T4 and T2 managements were higher than those in T3 and T1, respectively. Total water consumption amounts markedly raised in T1 and T3 managements, whereas their soil storage water amounts utilization declined. T2 and T4 managements reduced irrigation water amounts and optimized the water and fertilizer supplies, resulting in significant increase in WUES and WUEI. Collectively, our results suggest that synergetic improving the water uptake and utilization of irrigation water and soil storage water can be the primary means to increase the grain yields and WUE.

The aim of the present study was to investigate the clinical potential of transcription factor (TCF) 21 methylation in the diagnosis of renal cell carcinoma (RCC). TCF21 methylation levels were quantified in renal tissues (55 cases of RCC tissue and 22 cases of normal tissue) and urine samples (33 cases of urine samples with RCC and 15 cases of normal urine samples) using pyrosequencing. Spearman's rank correlation coefficient was used to investigate the correlation between TCF21 methylation levels and clinical parameters (gender, age, smoking history, Fuhrman grade and clinical stage). The receiver operating characteristic (ROC) curve was utilized to evaluate the accuracy of predictive diagnosis of RCC. TCF21 methylation levels were significantly increased in RCC samples compared with normal renal tissues and urine samples. The Spearman's correlation analysis revealed that the TCF21 methylation level was positively associated with age (P=0.002), smoking (P=0.017) and Fuhrman grade (P=0.045) in RCC tissues and was positively associated with tumor size (P

Increasing plant density has been an effective way for cotton yield improvements. The density of plants in a community also determines competition intensity and the efficiency to exploit available resources. However, the competition response as well as optimal density for yields and the mechanisms of which in terms of fruit growth rate are poorly known. A field experiment was conducted on cotton (Gossypium hirsutum L. SCRC 28) at a wide range of plant densities from 1.5–10.5 plants m−2. The results indicated that intraspecific competition between cotton plants increased nonlinearly with increasing plant density. Seedcotton yield per unit ground area declined precipitously at plant densities below the 4.0 plants m−2 threshold and yield did not further increase above this threshold, which is interpreted as the minimum plant density at which yield should be maximized. Moreover, maximum fruit production and fruit growth rate were also recorded at the same density threshold, above which there was no significant response. Cotton yield was positively correlated with fruit production and fruit growth rate. We thus conclude that high fruit production and fruit growth rate are responsible for maximum yield under optimal plant density in cotton.

Background: Studies on the prognostic role of von Willebrand factor (vWF) in patients with atrial fibrillation (AF) are conflicting. This meta-analysis aimed to evaluate the association of elevated circulating vWF level with adverse outcomes in patients with AF. Methods: PubMed and Embase were used to search literature through August 2017. Prospective observational studies that evaluated the association of elevated vWF level with major adverse cardiac events (MACEs) and all-cause mortality in patients with AF were deemed eligible. The MACEs included death, stroke/transient ischemic attack, heart failure, myocardial infarction, and systemic/peripheral embolism. Results: A total of 6 studies were included this meta-analysis. Patients with AF with the highest vWF level were independently associated with greater risk of MACEs (risk ratio [RR] 2.20; 95% confidence intervals [CI] 1.61–3.01) and all-cause mortality (RR 1.63; 95% CI 1.39–1.91). Subgroup analysis showed that the prognostic role of higher vWF level was consistently observed in each defined subgroups. Conclusion: Patients with AF with elevated vWF level are independently associated with a higher risk of MACEs and all-cause mortality. However, more well-designed prospective studies are needed to confirm these findings.

Primary aldosteronism (PA) is a rare disorder. The majority of patients with PA present with typical features and are easily diagnosed. This disorder is usually diagnosed with hypokalemia, hypertension or an adrenal mass. However, patients with atypical symptoms may present a challenge for diagnosis and treatment. In the present study, a case of PA is described that presented with hypokalemic myopathy simulating polymyositis. The patient was a 44-year-old woman who presented with weakness and difficulty walking. The patient was initially suspected to have PM and was treated with methylprednisolone. The patient was found to have hypokalemia which persisted despite high-dose supplementation of potassium. Adrenal computed tomography revealed a right adrenal mass. Surgical adrenalectomy was conducted. The final pathological diagnosis was benign adrenocortical adenoma. The serum tests remained normal and the patient's symptoms were resolved during the 8-month follow-up.