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The seasonal and interannual variabilities of sea surface wind (SSW) in the South China Sea (SCS), especially in coral reef regions such as Nansha Islands, Xisha Islands, Zhongsha Islands and Dongsha Islands were investigated in detail using the Blended Sea Winds dataset (1988–2017). Annual and monthly variations of SSW and sea surface temperature (SST) in the four zones were investigated. Empirical Orthogonal Function (EOF) analysis of wind field was performed to aid in better understanding the different spatial patterns. The results indicate that, as observed in the spatial distribution of the first mode of monthly mean wind speed anomaly, the magnitudes in the four island zones are all negative and are similar to each other, showing that the variations of SSW in the four island zones are consistent. In the second mode, the magnitudes in Nansha Islands are opposite to those in the other three zones. The spatial distribution of the third mode reflects regional differences. The maximum annual SSW appears in Dongsha Islands, and the minimum appears in Nansha Islands. The interannual variations of SSW in all island zones are basically concurrent. The island zones with high SSW mostly have low SST, and vice versa. There may be an inverse relationship between SSW and SST in coral reef regions in the SCS. The multi-year monthly variations of SSW in the island zones present a 'W'-shaped structural variation. Each island undergoes two months of minimum SSW every year, one during March–May (MAM) and the other during September–November (SON). Both months are in monsoon transition periods. During the months with low SSW, high SST appears. The SST peaks almost correspond to the SSW troughs. This further indicates that SSW and SST may have opposite changes in coral reef regions. Coral bleaching events often correspond to years of high SST and low SSW. [ABSTRACT FROM AUTHOR]

With the development of standardization and scaling in the dairy farming industry, timely and accurate pregnancy diagnosis is required to improve the benefits of breeding by shortening the calving interval. However, the current pregnancy diagnostic methods cannot meet the requirements of the industry. Here, we review changes in the physiological indexes and in the function and morphological status of the reproductive organs of dairy cows at the early stages of pregnancy. In addition, the corresponding pregnancy diagnostic methods based on certain indexes are well development, and the pregnancy diagnostic approaches based on remote sensing and automation technology have become inevitable trends in the industry. These applications will reveal physiological regularities in pregnancy and benefit the detailed management of dairy cows during early pregnancy. [ABSTRACT FROM AUTHOR]

Estrus identification is important in dairy cow production. At present, estrus identification is automated with a pedometer or accelerometer and the results remain unsatisfactory. It was previously reported that body temperature changes during estrus. In the present study, dairy cow vaginal temperature (VT) was monitored during various seasons, and an increase in VT of 0.3 °C was suggested for the onset of estrus, using an automated VT monitoring system developed in-house. Natural and synchronized estrus were measured simultaneously. The VT was determined to be in circadian rhythm and significantly higher in summer than in either autumn or winter (P < 0.05). VT difference (between estrus VT and average VT 7 days earlier) gradually increased, reached a peak of 0.56 °C ± 0.17 at 4 h before the end of estrus, and then decreased to the normal. The VT of cows in estrus and the duration of their estrus were significantly affected by seasons and estrus types (P < 0.05). VT gradually decreased in response to prostaglandin (PG) injection and was significantly lower (0.15–0.35 °C) from 9 to 33 h after the drug administration than the average VT at the same time 7 days earlier (P < 0.05). Changes in circadian and seasonal VT and in the estrous cycle can be monitored to assess the physiological status of cows and will help in developing an effective automated estrus identification technique. Results of this pilot study should be validated in further studies. [ABSTRACT FROM AUTHOR]