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Traditional orchard production is facing problems of labor shortage due to the aging, difficulties in the management of agricultural equipment and production materials, and low production efficiency which can be expected to be solved by building a smart orchard that integrates technologies of Internet of Things(IoT), big data, equipment intelligence, et al. In this study, based on the objectives of full mechanization and intelligent management, a smart orchard was built in Pinggu district, an important peaches and pears fruit producing area of Beijing. The orchard covers an aera of more than 30 hm2 in Xiying village, Yukou town. In the orchard, more than 10 kinds of information acquisition sensors for pests, diseases, water, fertilizers and medicines are applied, 28 kinds of agricultural machineries with intelligent technical support are equipped. The key technologies used include: intelligent information acquisition system, integrated water and fertilizer management system and intelligent pest management system. The intelligent operation equipment system includes: unmanned lawn mower, intelligent anti-freeze machine, trenching and fertilizer machine, automatic driving crawler, intelligent profiling variable sprayer, six-rotor branch-to-target drone, multi-functional picking platform and finishing and pruning machine, etc. At the same time, an intelligent management platform has been built in the smart orchard. The comparison results showed that, smart orchard production can reduce labor costs by more than 50%, save pesticide dosage by 30% ~ 40%, fertilizer dosage by 25% ~ 35%, irrigation water consumption by 60% ~ 70%, and comprehensive economic benefits increased by 32.5%. The popularization and application of smart orchards will further promote China's fruit production level and facilitate the development of smart agriculture in China.

BACKGROUND: The use of unmanned aerial vehicles (UAVs) for the application of plant protection products (PPPs) in paddy fields is becoming increasingly prevalent worldwide. Despite its growing usage, UAV spraying for rice pest control faces practical challenges, including limited canopy penetration, uneven deposition, and significant spray drift. This study investigated the impact of two tank‐mix adjuvants, Wonderful Rosin (Adjuvant‐1) and Tiandun (Adjuvant‐2), at six volume concentrations, on the spray liquid's physicochemical properties, spray drift, plant deposition, and the biological efficacy of rice insecticides using a quadrotor UAV sprayer. RESULTS: The physicochemical characteristics of the spray liquid influenced spray performance and biological efficacy. Incorporating Adjuvant‐1 and Adjuvant‐2 led to a decrease in surface tension and contact angle while increasing the viscosity of the spray solution. These alterations in surface tension and viscosity contributed to an optimized droplet size distribution, reduced spray drift, enhanced deposition uniformity and penetration, and improved control efficacy against the rice planthopper in UAV applications. The highest control efficacy was observed at a concentration of 0.5%, showing an improvement of 35.12% (Adjuvant‐1) and 20.23% (Adjuvant‐2) over applications without tank‐mix adjuvant 7 days after treatment. CONCLUSION: The judicious selection of tank‐mix adjuvants for UAV PPP applications can significantly enhance spray performance and biological efficacy in controlling rice insects. This study's findings offer valuable insights for integrating tank‐mix adjuvants into UAV spraying applications. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Extensive research has been conducted on the effects of pollen activation temperature, cultivation temperature, and ambient temperature on germination rates and fruit sets. Yet, the influence of the temperature (pre-germination temperature) at which the pollen suspension is prepared within the storage container (tank) remains unexplored. In this study, we initially established the optimal time for pollen activation. Subsequently, pollen suspensions at varying temperatures were prepared, and their germination rates were analyzed using microscopy. Pollen suspensions of different temperatures were then sprayed onto Fojianxi pear flowers, and parameters such as flower fruit set rate, inflorescence fruit set rate, fruit longitudinal dimension, fruit transverse dimension, and fruit shape index were evaluated. The findings revealed that the optimal pollen activation duration was 6 h. A pollen suspension temperature of 30 °C resulted in the highest germination rate (72.06 ± 6.87%). However, a suspension temperature of 25 °C achieved the highest flower fruit set rate (57.29 ± 5.58%) and inflorescence fruit set rate (87.50 ± 4.84%). The fruit longitudinal dimension (68.12 ± 3.94 mm), transverse dimension (73.77 ± 4.04 mm), and fruit shape index (108.42 ± 6.02%) were most favorable at a suspension temperature of 15 °C. Our study concludes that the pollen in lower pollen suspension temperatures (15~25 °C) has higher germination energy and have higher stigmatic capacity. Thus, we advocate for a pollen suspension temperature range of 15~25 °C when employing liquid spray pollination techniques with Xuehuali (Pyrus bretschneiderilia) pollen. [ABSTRACT FROM AUTHOR]

There is an urgent need for new chemical application techniques and sprayers in Chinese orchard spraying. A new tractor-mounted automatic target detecting electrostatics, and air-assisted orchard sprayer was designed and developed to meet the demand of chemical pest control in orchards. This sprayer light weighted, highly efficient, reduces pesticide use and is friendly to the environment. The techniques of automatic target detecting, electrostatics, and air-assisted spraying were combined in this system. The electrostatically charged droplets are projected toward the target by the assistance of an air stream that increases the droplets penetration within canopy. Experimental results show that the new automatic target detecting orchard sprayer with an infrared sensor can save more than 50% to 75% of pesticides, improve the utilization rate (over 55%), control efficiency, and significantly reduce environmental pollution caused by the pesticide application. At the same time the key technological problems related to air-assisted low volume and electrostatic spraying were solved. [ABSTRACT FROM AUTHOR]

Objective: Metformin reduces incidences of miscarriage and preterm delivery in polycystic ovary syndrome (PCOS) women, but its impact on gestational diabetes mellitus (GDM) is conflicting. Hence, this study set up selection criteria to include previously infertile women with PCOS but without pre-existing DM who became pregnant, aiming to minimize confounders and investigate the influence of metformin on GDM, miscarriage, and preterm delivery., Methods: This study included 195 previously infertile women with PCOS who became pregnant. They were divided into metformin (receiving metformin during pregnancy) and control (not receiving metformin) groups without intervention., Results: Metformin group tended to have a lower incidence of GDM versus control group (13.3% versus 23.3%, P = 0.070). A logistic regression model adjusted for all baseline characteristics (demographics, infertile duration, and diabetes mellitus-related features) showed that metformin was associated with a decreased probability of GDM (odds ratio (OR): 0.426, P = 0.037). Metformin group showed a similar incidence of miscarriage (6.7% versus 11.1%, P = 0.273), but decreased incidences of preterm delivery (not statistically significant) (6.7% versus 13.3%, P = 0.091) and miscarriage or preterm delivery (13.3% versus 24.4%, P = 0.046) versus control group. A logistic regression model adjusted for all the aforementioned features revealed that metformin was related to a lower risk of miscarriage or preterm delivery (OR: 0.417, P = 0.040). Fetal outcomes, including birth weight (P = 0.245) and the incidence of 5 min-Apgar score ≤ 7 (P = 0.702), were similar between groups., Conclusion: Metformin administration during pregnancy may reduce GDM, miscarriage, and preterm delivery risks without adverse effects on fetal outcomes in previously infertile women with PCOS., (© 2024. The Author(s), under exclusive licence to Royal Academy of Medicine in Ireland.)