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BACKGROUND In‐field weed detection in wheat (Triticum aestivum L.) is challenging due to the occurrence of weeds in close proximity with the crop. The objective of this research was to evaluate the feasibility of using deep convolutional neural networks for detecting broadleaf weed seedlings growing in wheat. RESULTS The object detection neural networks, including CenterNet, Faster R‐CNN, TridenNet, VFNet, and You Only Look Once Version 3 (YOLOv3) were insufficient for weed detection in wheat because the recall never exceeded 0.58 in the testing dataset. The image classification neural networks including AlexNet, DenseNet, ResNet, and VGGNet were trained with small (5500 negative and 5500 positive images) or large training datasets (11 000 negative and 11 000 positive images) and three training image sizes (200 × 200, 300 × 300, and 400 × 400 pixels). For the small training dataset, increasing image sizes decreased the F1 scores of AlexNet and VGGNet but generally increased the F1 scores of DenseNet and ResNet. For the large training dataset, no obvious difference was detected between the training image sizes since all neural networks exhibited remarkable classification accuracies with high F1 scores (≥0.96). All image classification neural networks exhibited high F1 scores (≥0.99) when trained with the large training dataset and the training images of 200 × 200 pixels. CONCLUSION CenterNet, Faster R‐CNN, TridentNet, VFNet, and YOLOv3 were insufficient, while AlexNet, DenseNet, ResNet, and VGGNet trained with a large training dataset were highly effective for detection of broadleaf weed seedlings in wheat. © 2021 Society of Chemical Industry.

Abstract:Canopy transpiration is an important component of evapotranspiration, integrating physical and biological processes within the water and energy cycles of forests. Quercus acutissima and Cunninghamia lanceolata are two important, fast-growing and commercial tree species that have been extensively used for vegetation restoration, water conservation and building artificial forests in the Yangtze River Delta region of China. The primary objective of this study was to characterize sap flow densities of the two species by comparing daytime and nocturnal sap flow patterns and their relationships with environmental factors. Sap flow densities (S d ) were measured between September 2012 and August 2013 using the commercially-available thermal dissipation probes. Hourly meteorological data were measured in an open field, located 200 m away from the study site, including photosynthetically-active radiation (P ar ), air temperature (T a ), relative air humidity (R h ), vapor pressure deficit (V pd ) and precipitation (P). Soil water content (S wc ) data were logged hourly in different layers at Q. acutissima and C. lanceolata forests. Results indicated that the mean S d in summer was higher than that in spring and autumn. Both the S d of Q. acutissima and C. lanceolata showed distinct diurnal patterns. Nocturnal sap flow densities (S dn ) were noticeable, and both species followed similar declining patterns during our study period. The daytime sap flow density (S dd ) was more sensitive to environmental factors than S dn . Sap flow density was significant linearly correlated with P ar , V pd and T a , and P ar and V pd explained the greatest amount of variation in daytime sap flow of Q. acutissima and C. lanceolata, respectively. Our study will enrich knowledge of plantation forest physical and biological processes and provide valuable information for plantation forest management in the Yangtze River Delta region of China.

Up to now very few case studies have provided evidence of the effect of large regional increases in forest area on improving regional climate. This article is perhaps the first description of a unique positive case study of the increasing protection provided by reforestation in controlling a formerly disastrous climate, where gale days have decreased by 80 % per year, and maximum wind speeds of gales have decreased on average from 26 to 11 m/s, while overall average annual wind speed has decreased by 90 % near the ground surface when forest coverage has increased from 3 % in 1950s to 36.9 % in 2010s within 60 years, changing the long-term trend of sandstorms and desertification into a wetter climate where disastrous droughts are now rare despite a global megatrend of decreasing forest area and climate warming. The local climate has been improved by reducing the extreme highs in temperature, reducing the power and frequency of gales, and increasing the number of foggy days. Thus, we propose in arid and semi-arid regions, billions of trees may have a direct effect on improving regional climate, which is worth attention to more than just because of its function as a carbon sink.Keywords Forest shelter belt Á Regional climate change Á Average annual wind speed Á Number of foggy days

Bone biomineralization is well-regulated processes mediated by extracellular matrix proteins. The materials that can direct nucleation of hydroxylapatite (HAp) crystals and assembly of well-structured material-minerals complex are the key to mimicking the natural mineralization. This study used sericin from Antheraea pernyi (A.pernyi), non-mulberry silkworm cocoon as template to mediate nucleation of HAp crystals. Here we find out that AS (Antheraea pernyi sericin) can nucleate the formation HAp crystals in simulated body fluid verified by XRD and FTIR observations. The HAp crystals are organized into nano-rods oriented with c-axis preferentially parallel to the long axis of AS due to hydrogen bonds and electrostatic interaction and finally aggregated into HAp globule. The cell culture of human bone marrow-derived mesenchymal stem cells (BMSCs) showed that the HAp crystals mediated by AS not only stimulate cell adhesion and proliferation but also promote 0f osteogenic differentiation, suggesting that the resultant mineralized AS biomaterial has potential in promoting bone formation. Thus our work will provide significant implication on biomineralization of A. pernyi silk sericin as a potential scaffold for tissue engineering.