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Applying cover crops to reduce nitrogen (N) fertilizer application while ensuring crop productivity is a major challenge for sustainable agricultural production. However, few studies have quantified N fertilizer application reduction through the use of February orchid (Orychophragmus violaceus) cover crops with the goal of ensuring cotton productivity. We conducted field experiments in the Yellow River basin on two cropping systems, monoculture cotton (Gossypium hirsutum L) and cotton/February orchid under four levels of N application (0 [N0], 112.5 [N1], 168.75 [N2], and 225 [N3] kg N·ha−1), to evaluate the impacts of cover cropping on cotton growth parameters, yield, and quality under different N application levels. The results indicated that replacing winter fallow with February orchid prolonged the cotton growth period and increased plant height, leaf area index (LAI), and dry matter accumulation but did not improve cotton yield or fiber quality. The Cotton/February orchid system under a 168.75 kg ha−1 N application rate improved cotton growth, and achieved yield and quality equivalent to those of monoculture cotton under a 225 kg ha−1 N application. Further analysis revealed that February orchid cover crop and N application positively affected lint yield, whereas plant height, LAI, and dry matter accumulation (positively) and phenology (negatively) predicted lint yield and fiber quality. In conclusion, cotton relay intercropping with February orchid in combination with 168.75 kg ha−1 N application is recommended as a suitable cropping system to reduce fallow fields and ensuring cotton productivity in the Yellow River basin and other areas with similar ecological conditions. Core Ideas: Replacing winter fallowing of fields with February orchid cultivation improved cotton growth parameters.Improvement in cotton growth and productivity with increasing nitrogen application rates.Relationships among cotton phenology, agronomic traits, yield, and quality were quantified.February orchid combined with 75% N fertilizer ensured cotton biomass and yield. [ABSTRACT FROM AUTHOR]

Determining the optimal plant architecture and canopy structure are important objectives in research on the breeding and cultivation of high-yielding crops. To address this challenge, a field experiment was conducted in Anyang, Henan, China, to assess cotton light interception, boll spatial distribution, leaf area index (LAI), plant height and biomass, lint yield and yield component during 2018–2019. Treatments including 10 cotton cultivars with belong to tower-shaped and tube-type canopy structure. Compared with compact cotton varieties, the loose and tower-shaped cotton varieties intercepted more light (average 28.6%) and had a higher LAI (average 34.2%), resulting in a higher cotton yield (average 14.8%). In addition, polynomial correlation showed that the maximum light interception rate occurred at the flowering and boll-forming stage, when the annual mean plant height (94.6 cm), LAI (3.58) and biomass (15,006 kg ha−1) all reached their peak. Moreover, yield was extremely significantly positively correlated with intercepted photosynthetically active radiation (IPAR) (R = 0.7) and positively correlated with light use efficiency (LUE) (R = 0.36). Overall, the results suggest that cotton cultivars with loose and tower-type canopy structures intercept more light and should be planted to increase cotton yield and LUE in the Yellow River basin of China and areas with similar conditions. [ABSTRACT FROM AUTHOR]

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 productivity, while the effect of cover crops on soil quality and cotton productivity remains unclear in the region. Using a monoculture cotton (cotton-fallow) as the control, a field experiment was conducted to verify the impacts of cotton with two cover crops, Orychophragmus violaceus (cotton/O. violaceus) and Vicia villosa (cotton/V. villosa), on soil chemical properties and cotton productivity. The results showed that cotton/O. violaceus increased the soil organic matter (SOM), total nitrogen (TN), and available nitrogen (AN) by 5.77%, 2.03%, and 13.07% compared to cotton-fallow at a 0–100 cm soil depth, respectively. Cotton/O. violaceus developed relatively greater cotton biomass accumulation and higher cotton yield than cotton/V. villosa and cotton-fallow, an immediate cause of which was greater reproductive organ biomass accumulation and a larger number of bolls per unit area. Furthermore, SOM and TN had a significantly positive correlation with cotton biomass and yield. Cotton/O. violaceus were more conducive than cotton/V. villosa and cotton-fallow in the Yellow River basin of China and in other areas with similar requirements. [ABSTRACT FROM AUTHOR]

Volumetric soil water content (VSWC) monitoring is an important aspect of environmental monitoring of farmland. Accurate and real-time determination of the VSWC is important for crop drought stress diagnosis and smart irrigation. Image technology is commonly used in agricultural information technology. Based on image technology, we simulated the optimal frequency of the sensors to automatically collect VSWC data, thereby solving the problems of data redundancy and data analysis difficulties in real-time monitoring. In this study, a cotton field under mulched drip irrigation in 2018 was utilised as the research subject, 5TE sensors were arranged on the soil profile of the cotton field using the "grid method", and Voxler and Surfer software was used to model the VSWC data and draw contour maps. Image processing technology (image greyscale and image similarity comparison) was employed to determine the image algorithm suitable for contour map pre-processing and the best time period for VSWC monitoring. These results indicated that the contrast-limited adaptive histogram equalisation (CLAHE) greyscale algorithm is a suitable pre-processing algorithm for processing contour maps using image processing technology, and the best 5TE sensor data monitoring time period is every 10 h. This conclusion provides a theoretical reference for VSWC monitoring and water management in production. • Image technology can be used for VSWC data processing. • CLAHE is a suitable greyscale algorithm for VSWC contour maps. • The longest interval for acceptable VSWC data with 5TE was 10 h. [ABSTRACT FROM AUTHOR]