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Copyright of Journal of Agro-Environment Science is the property of Journal of Agro-Environment Science Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The accuracy of the rolling time when the tube head and tail enter the stretch reducing mill (SRM) is very important to the accuracy of the model for SRM crop end control (CEC). Since it is difficult to install the sensor to detect the wall thickness of the tube head and tail to get effective feedback mechanism, the application efficiency of the said model is reduced. It is suggested to introduce the torque of the roll motor as the basis for the judgment of the feedback of tube bite and casting, and meanwhile to introduce the function of tracking tube head and tail so as to filter the surplus torque fluctuation. Based on the actually-measured time for tube bite and casting, the data are sent into the queue to calculate the moving average value of the CEC correction value so as to get the CEC model accurately trigged as per the time for tube bite and casting to reduce the crop loss. The feasibility of this method is verified via relevant practice. [ABSTRACT FROM AUTHOR]

Autonomous navigation is an important guarantee for intelligent agricultural machinery to complete harvesting operations. Navigation line recognition is an important step in achieving autonomous navigation of intelligent agricultural machinery. Real-time and accurate detection of harvesting navigation lines can effectively accelerate the progress of operations and reduce crop loss rates. Visual sensors have the advantages of low cost and rich information acquisition, making them widely used in route detection. Frequent changes in lighting under cloudy weather make it difficult for a single feature to cope with wheat field environments. In this study, a wheat harvesting boundary detection method based on multi texture feature fusion was proposed. In the harvested area, the characteristics of low stubble and no top wheat ears result in differences in uniformity, density, and other aspects when harvesting under both light and backlight compared to the non-harvested area. At the same time, due to the exposed wheat stubble in the harvested area, it appears more regular on the image, and its gradient direction is more consistent than that in the non-harvested area. Therefore, a two-dimensional feature vector composed of image entropy and directional gradient was constructed to classify the harvested and unharvested areas of the wheat field, and then the harvesting boundary was extracted. Due to the susceptibility of image entropy features to perspective phenomena, this paper compared the entropy features of different regions in the image when fixing the camera installation angle and height, and ultimately selected the middle region of the image as the region of interest. After analyzing the characteristics of image entropy feature extraction, a histogram statistical method based on sliding windows was proposed to accelerate the speed of image entropy feature extraction. By further dividing the window to be calculated into several sub windows, sliding and combining these sub windows significantly reduced the computation. The entropy feature extraction in this paper took 0.53 seconds, which is 49.52% faster than the traditional method of directly extracting entropy from the entire window. After extracting twodimensional features, based on the distribution characteristics of the feature histogram and combined with the maximum entropy threshold segmentation algorithm, the wheat field image was preliminarily classified. For entropy features, low noise points affected the threshold segmentation effect. By comparing the impact of discarding different proportions of low entropy points on the segmentation threshold, this paper discarded 10% of low entropy points, enhancing the threshold segmentation effect. The method of removing small connected regions was used to eliminate the misclassified regions in the initial classification binary image. Then, the Canny operator was used to extract edge contour points distributed near the harvesting boundary. Due to the consistent direction between the harvesting boundary and the agricultural machinery's forward direction, the Ransac algorithm was used to restrict the fitting line in the region, obtaining the accurate harvesting boundary. In order to verify the feasibility of the method proposed in this article, wheat field images under different lighting conditions were collected, including 2 200 weak light images, 758 local strong light images, and 1 134 strong light images. After selecting the region of interest, the size of the image to be processed was 240 pixels×1 280 pixels. The algorithm in this paper took an average of 0.88 s to process each image on laptops. The detection rates under weak light, local strong light, and strong light were 90.41%, 88.26%, and 89.68%, respectively, with an average of 89.45%. Compared with the traditional method of using Adaboost algorithm for machine learning, the detection speed of this algorithm was improved by 73.89%, and the detection rate was increased by 46.19 percentage points, 46.00 percentage points, and 49.64 percentage points under weak light, local strong light, and strong light, respectively. Compared with traditional algorithms, the method proposed in this paper significantly improved real-time performance and detection rate, which can provide reference for the detection of field agricultural machinery navigation lines. [ABSTRACT FROM AUTHOR]

Barnyardgrass (Echinochloa crus-galli) is one of the most problematic weeds infesting rice fields and causes huge crop yield losses. To clarify the resistance pattern and possible mechanisms of resistance in barnyardgrass population JS12 in Jiangsu Province, whole-plant dose-response experiments were conducted to determine the sensitivity to metamifop, and its target- and non-target based mechanisms were clarified by gene sequencing and expression analysis of ACCase gene, as well as synergistic effects on resistance of two metabolic enzyme inhibitors. Finally, the sensitivities of JS12 population to ACCase inhibitors and other herbicides with different modes of action were analyzed to determine the cross- and multi-resistance patterns. Results showed that the JS12 population exhibited 13.71 times high-level resistance to metamifop. No amino acid substitutions conferring metamifop resistance were detected in six copies of ACCase genes in JS12 population, and the gene expression levels of ACCase were significantly lower than that of the susceptible population after herbicide treatment. Both cytochrome P450 inhibitor malathion and glutathione-S-transferase (GST) inhibitor NBD-Cl could significantly increase the susceptibility of JS12 population to metamifop, causing the GR50 (herbicide rate causing growth reduction by 50%) value to decrease from 227.90 g/hm² to 77.51 g/hm2 and 137.93 g/hm², respectively. In addition, the resistant population JS12 had evolved cross-resistance to ACCase inhibitors cyhalofop-butyl, fenoxaprop-p-ethyl, clethodim, and pindoxaden, and multi-resistance to acetolactate synthase (ALS)-inhibiting herbicide penoxsulam and auxin herbicide quinclorac. Nevertheless, it was still susceptible to the new herbicides florpyrauxifen-benzyl and triadimefon. This study suggested that the enhanced herbicide metabolism mediated by cytochrome P450 and GST might be an important reason for herbicide resistance in JS12 population. Florpyrauxifen-benzyl and triadimefon can be used to control the resistant population. [ABSTRACT FROM AUTHOR]

According to the observed meteorological data in 2022 and the historical data from 2467 meteorological stations in China, the agrometeorological evaluation index, the climate suitability degree model and agrometeorological disaster index model were used to evaluate the agrometeorological effects on yield of major autumn harvest crops, such as corn, single rice, later rice, soybean and cotton. The results showed that: the light conditions and thermal conditions were sufficient for crop growth and development in the growing season. The precipitation and soil water conditions were non-uniform distribution in time and space, which restricted the yield increase of corn, rice, soybean and other crops. The impact of low temperature, sunless, continuous rain, rainstorm and flood disasters during the main growth period was light, while the meteorological conditions were favorable for crop development growth and yield. The comprehensive intensity of high temperature in summer in the Yangtze River basin reached the highest level since 1961. The single rice during filling maturation suffered heat injury, while the corn suffered continuous drought in summer and autumn. The rainstorm disasters occurred frequently especially Jilin, Liaoning and Shandong provinces which caused the crops to heavy losses, and some crops were out of harvest. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Agricultural Outlook (1673-3908) is the property of Institute of Agricultural Information, Chinese Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Oil Crop Sciences is the property of Oil Crops Research Institute of Chinese Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Agro-Environment Science is the property of Journal of Agro-Environment Science Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Agricultural Science & Technology (1008-0864) is the property of Journal of Agricultural Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The abnormal first frost date and last frost date that occur in the critical period of crop growth will cause great losses to crop yields. It is of great significance to know and grasp the changing rules of abnormal frost date index accurately in the Huaihe River Basin to ensure the stable, high and safe grain yield of China. Ground 0 cm daily minimum temperature collected at 61 meteorological stations were used to identify the first and the last frost dates. The standard deviation was used to calculate the stability of the first and the last frost dates and the probability density function was used to define abnormal first and last frost dates. Meanwhile, IDW interpolation method was adopted to reflect the stability of first and last frost dates and the frequency of abnormal frost date before and after the transition of climate state. Moreover, linear trend estimation, Mann-Kendall mutation test, sliding t- test and cumulative averaging method were employed to obtain the mutation year in temperature. And the effect of the circulation index and air temperature on the first and the last frost dates was analyzed by correlation coefficient method. The following conclusions can be drawn from the analysis above: (1) The mean temperature of Huaihe River Basin in the period 1960- 2015 showed a significant upward trend at a rate of 0.18 °C· 10 a-1 (P<0.01) and the mutation year happened in 1993. The transition of climate state promoted the postponement of the first frost date and the advancement of the last frost date. (2) The transition of climate state led to the decrease of the stability of first and last frost dates. The stability of first and last frost dates became much better with the increase of latitude and longitude. The stability of the first frost date became better with the increase of elevation. But the change of the last frost date is not significant even when the elevation increases. The stability of the last frost date is better than that of the first frost date. (3) There was a descending order among the frequency of earlier first frost date, later last frost date, special early first frost date, and special late last frost date. And after the transition of climatological state, the frequency of abnormal first and last frost days tends to decrease and be stable at 0-20%. On the whole, the frequency of abnormal first frost date is higher than that of abnormal last frost date. The impact of climate warming is greater on the first frost date than on the last frost date. (4) The spatial distribution of abnormal first and last frost dates was significantly different, the high frequency of which was observed in the 1970s and the 1960s, respectively, and the low frequency of which was found in the 2000s. Although the frequency of abnormal first and last frost dates was gradually stabilized and remained at a low level, the transition of climate promoted the increase of the frequency of special early first date in the southeast and south parts, partial early first frost date in the south, partial late last frost date in the northeast, and special late frost date in the southeast of the Huaihe River Basin respectively. (5) The smaller the polar vortex area is in September in the northern hemisphere, the later the first frost date is (R=- 0.41, P< 0.01); the smaller the polar vortex area is in February, the earlier the last frost date would be (R=0.29, P<0.01); the larger the subtropical high is in October, the later the first frost date is (R=0.39, P<0.05); the larger the subtropical high is in April, the earlier the last frost date is (R=-0.15, P>0.05). Moreover, the tendency ahead of schedule was accelerated after 1990. The result of this article is good for frost forecast services and mitigation of frost disasters. [ABSTRACT FROM AUTHOR]