[Grain yield estimation of wheat-maize rotation cultivated land based on Sentinel-2 multi-spectral image: A case study in Caoxian County, Shandong, China]. / 基于Sentinel-2å¤šå ‰è°±å½±åƒçš„å°éº¦-玉米轮作耕地粮食产量估测­­ä»¥æ›¹åŽ¿ä¸ºä¾‹.

Establishing the remote sensing yield estimation model of wheat-maize rotation cultivated land can timely and accurately estimate the comprehensive grain yield. Taking the winter wheat-summer maize rotation cultivated land in Caoxian County, Shandong Province, as test object, using the Sentinel-2 images from 2018 to 2019, we compared the time-series feature classification based on QGIS platform and support vector machine algorithm to select the best method and extract sowing area of wheat-maize rotation cultivated land. Based on the correlation between wheat and maize vegetation index and the statistical yield, we screened the sensitive vegetation indices and their growth period, and obtained the vegetation index integral value of the sensitive spectral period by using the Newton-trapezoid integration method. We constructed the multiple linear regression and three machine learning (random forest, RF; neural network model, BP; support vector machine model, SVM) models based on the integral value combination to get the best and and optimized yield estimation model. The results showed that the accuracy rate of extracting wheat and maize sowing area based on time-series features using QGIS platform reached 94.6%, with the overall accuracy and Kappa coefficient were 5.9% and 0.12 higher than those of the support vector machine algorithm, respectively. The remote sensing yield estimation in sensitive spectral period was better than that in single growth period. The normalized differential vegetation index and ratio vegetation index integral group of wheat and enhanced vegetation index and structure intensify pigment vegetable index integral group of maize could more effectively aggregate spectral information. The optimal combination of vegetation index integral was difference, and the fitting accuracy of machine learning algorithm was higher than that of empirical statistical model. The optimal yield estimation model was the difference value group-random forest (DVG-RF) model of machine learning algorithm (R2=0.843, root mean square error=2.822 kg·hm-2), with a yield estimation accuracy of 93.4%. We explored the use of QGIS platform to extract the sowing area, and carried out a systematical case study on grain yield estimation method of wheat-maize rotation cultivated land. The established multi-vegetation index integral combination model was effective and feasible, which could improve accuracy and efficiency of yield estimation.

Spontaneous remission of hepatic myelopathy in a patient with alcoholic cirrhosis: A case report.

BACKGROUND: Hepatic myelopathy (HM) is a rare neurological complication of advanced cirrhosis. Prognosis of patients with HM is generally poor without timely liver transplantation or interventional therapy. Self-resolving HM in patients with alcoholic cirrhosis has never been reported. CASE SUMMARY: A 53-year-old man with alcoholic cirrhosis and recurrent overt hepatic encephalopathy for 1 year was admitted for lower extremity weakness, slow movement, and stumbling gait. The patient was diagnosed with HM after excluding other causes of spastic paraparesis. The patient refused liver transplantation. However, the patient kept total abstinence and received a multidisciplinary treatment for complications of decompensated cirrhosis. The symptoms of HM resolved gradually after 2 years of treatment. All complications of alcoholic cirrhosis resolved after 4 years of follow-up. CONCLUSION: The case demonstrates that HM can resolve in patients without liver transplan-tation after total abstinence and systemic management of complications.

Plant secondary metabolite and temperature determine the prevalence of Arsenophonus endosymbionts in aphid populations.

Transmission rate and role in hosts contribute to the prevalence of an endosymbiont. However, factors affecting transmission and role of facultative endosymbionts are still not well understood. Here, we illustrated that host plants and environmental temperatures affected the transmission, relative abundance and role of Arsenophonus in the cotton aphid Aphis gossypii. The transmission rate of this endosymbiont from mother aphids to offspring was relatively lower. High temperatures impeded the transmission, and infection rates declined as aphids were exposed to 30°C. Contents of amino acids and secondary metabolites were remarkably different among host plants. Aphids feeding on zucchini leaves containing a higher titre of amino acids and lower secondary metabolites harboured a relatively lower abundance of Arsenophonus. Concentrations of an amino acid and a plant secondary metabolite, cucurbitacin B, in aphid diet were not associated with Arsenophonus abundance. However, gossypol, another plant secondary metabolite, was strongly related with the abundance. Arsenophonus imparted a fitness benefit to aphids, and the benefit was dependent on host plants and gossypol concentration. In sum, plant secondary metabolite and environmental temperature affect transmission, relative abundance and role of Arsenophonus, which determine the endosymbiont prevalence in aphid populations.

The host range of Aphis gossypii is dependent on aphid genetic background and feeding experience.

BACKGROUND: A polyphagous insect herbivore has a wide range of host plants. However, it has been found that many polyphagous herbivores commonly exhibit a strong preference for a subset of species in their broad host range, and various host biotypes exist in herbivore populations. Nutrition and secondary metabolites in plants affect herbivore preference and performance, but it is still not clear which factors determine the host range and host preference of polyphagous herbivores. METHOD: Cotton-melon aphids, Aphis gossypii Glover, collected from cotton and cucumber crops, were used in this study. The genetic backgrounds of these aphids were detected using microsatellite PCR and six genotypes were evaluated. Performance of these six aphid genotypes on excised leaves and plants of cotton and cucumber seedlings were examined through a reciprocal transplant experiment. In order to detect whether the feeding experience on artificial diet would alter aphid host range, the six genotypes of aphids fed on artificial diet for seven days were transferred onto cotton and cucumber leaves, and then their population growth on these two host plants was surveyed. RESULTS: Aphids from cotton and cucumber plants could not colonize the excised leaves and intact plants of cucumber and cotton seedlings, respectively. All six genotypes of aphids collected from cotton and cucumber plants could survive and produce offspring on artificial diet, which lacked plant secondary metabolites. The feeding experience on the artificial diet did not alter the ability of all six genotypes to use their native host plants. However, after feeding on this artificial diet for seven days, two aphid genotypes from cotton and one from cucumber acquired the ability to use both of the excised leaves from cucumber and cotton plants. The two aphid genotypes from cotton conditioned by the feeding experience on artificial diet and then reared on excised cucumber leaves for >12 generations still maintained the ability to use intact cotton plants but did not establish a population on cucumber plants. However, one cucumber genotype conditioned by artificial diet and then reared on excised cotton leaves could use both the intact cotton and cucumber plants, showing that the expansion of host range was mediated by feeding experience. CONCLUSION: Feeding experience on artificial diet induced the expansion of host range of the cucurbit-specialized A. gossypii, and this expansion was genotype-specific. We speculated that feeding on a constant set of host plants in the life cycle of aphids may contribute to the formation of host specialization.

Infections with Arsenophonus Facultative Endosymbionts Alter Performance of Aphids (Aphis gossypii) on an Amino-Acid-Deficient Diet.

Genetic polymorphism and endosymbiont infection are ubiquitous in aphid populations. It has been known that the obligate symbiont Buchnera provides aphids with essential amino acids which cannot be ingested from plant sap. Buchnera often coexists with facultative endosymbionts in aphids. However, it is unclear whether the facultative endosymbionts affect the aphid's amino acid requirements from diet. In this study, we found that the facultative endosymbiont status in populations of the cotton-melon aphid Aphis gossypii was associated with aphid genotype or host plant. The infection frequency of Arsenophonus in aphids living on cotton was significantly higher than that in aphids on cucumber, and cucumber leaves contained higher titers of free amino acids than cotton leaves, especially amino acids Leu, Arg, Ile, Val, and Phe. The net reproductive rates of five aphid genotypes infected with Arsenophonus were not different on the complete-amino-acid diet, but the values were significantly different among seven Arsenophonus-free aphid genotypes. Moreover, the net reproductive rates of aphids on the amino-acid-deficient diet were significantly affected by Arsenophonus infection and aphid genotype. Arsenophonus infection decreased aphid performance on the Phe-free diet but improved performance on the Leu-free diet and did not affect the performance on the Ile-free or Val-free diet. Arsenophonus infections altered aphid requirements for amino acids that were significantly different in cotton and cucumber leaves, suggesting this endosymbiont would modulate the host specialization of this aphid.IMPORTANCE The facultative endosymbiont Arsenophonus plays an important role in regulating reproduction through son killing, enemy resistance, and the dietary breadth of its insect hosts. In this study, we found Arsenophonus could alter aphid performance on the amino-acid-deficient diets. Arsenophonus infection increased aphid requirements for the amino acid Phe, but decreased requirements for the Leu. Cotton and cucumber leaves contained drastically different titers of free amino acids Phe and Leu, and aphids living on these two plants were infected with different incidences of Arsenophonus We hypothesize that host specialization or the host plant range of aphids may be mediated by Arsenophonus.

[Land salinization information extraction method based on HSI hyperspectral and TM imagery].

This paper chose the typical salinization area in Kenli County of the Yellow River Delta as the study area, selected HJ-1A satellite HSI image at March 15, 2011 and TM image at March 22, 2011 as source of information, and pre-processed these data by image cropping, geometric correction and atmospheric correction. Spectral characteristics of main land use types including different degree of salinization lands, water and shoals were analyzed to find distinct bands for information extraction Land use information extraction model was built by adopting the quantitative and qualitative rules combining the spectral characteristics and the content of soil salinity. Land salinization information was extracted via image classification using decision tree method. The remote sensing image interpretation accuracy was verified by land salinization degree, which was determined through soil salinity chemical analysis of soil sampling points. In addition, classification accuracy between the hyperspectral and multi-spectral images were analyzed and compared. The results showed that the overall image classification accuracy of HSI was 96.43%, Kappa coefficient was 95.59%; while the overall image classification accuracy of TM was 89.17%, Kappa coefficient was 86.74%. Therefore, compared to multi-spectral TM data, the hyperspectral imagery could be more accurate and efficient for land salinization information extraction. Also, the classification map showed that the soil salinity distinction degree of hyperspectral image was higher than that of multi-spectral image. This study explored the land salinization information extraction techniques from hyperspectral imagery, extracted the spatial distribution and area ratio information of different degree of salinization land, and provided decision-making basis for the scientific utilization and management of coastal salinization land resources in the Yellow River Delta.

[Satellite remote sensing retrieval of canopy nitrogen nutritional status of apple trees at blossom stage].

Taking Qixia City of Shandong, China as the study area, and based on the Landsat-5 TM and ALOS AVNIR-2 images, the canopy retrieval reflectance of apple trees at blossom stage was acquired. In combining with the measured reflectance of sample trees, the nitrogen-sensitive spectral indices were constructed and selected. By using the sensitive spectral indices as the independent variables, the nitrogen retrieval models were established, and the model with the best accuracy was used for spatial retrieve. The correlations between the spectral indices and the nitrogen nutritional status were in the order of canopy > leaf > flower. The sensitive indices were mainly composed of green, red, and near infrared bands. The accuracy of the retrieval models was in the order of support vector regression > multi-variable stepwise regression > one-variable regression. The retrieval results based on different images were similar, and showed that the leaf nitrogen content was mainly of grades 3-4 (27-33 g x kg(-1)), and the canopy nitrogen nutrient indices were mainly of grades 2-4 (TM: 38-47 g x kg(-1); ALOS: 32-41 g x kg(-1)). The spatial distribution of the retrieval nitrogen nutritional status based on different images also showed the similar trend, i. e., the nitrogen nutritional status was higher in the north and south than that in the middle part of the study area, and the areas with the high grades of leaf nitrogen and canopy nitrogen were mainly located in Sujiadian Town and Songshan subdistrict in the northwest, Zangjiazhuang Town and Tingkou Town in the northeast, and Shewopo Town in the south, which were consistent with the distribution of the key towns for apple production in Qixia City. This study provided a feasible method for the acquisition of nitrogen nutritional status of apple trees on macroscopic scale, and also, provided reference for other similar remote sensing retrievals.

[Quantitative remote sensing retrieval of apple tree canopy reflectance at blossom stage in hilly area].

By using the TM and ALOS images with different resolutions at the prosperous blossom stage of apple trees in Qixia City of Shandong Province, and taking the slope aspect coefficient and the ratio of canopy flower to leaf into account, the ground surface reflectance was retrieved through radiometric correction. The canopy reflectance of the apple trees was further retrieved by pixel unmixing method, and the retrieval effect and accuracy were assessed by the comparison of the retrieved reflectance with the measured canopy reflectance and apparent reflectance of 30 sample apple orchards. The results showed that radiometric correction effectively weakened the effects of atmosphere and topography, recovered the ground objects in the shadows, and obviously enhanced the analytical ability of ground surface retrieval reflectance images. Either TM or ALOS images, both the absolute and relative errors between retrieval reflectance and measured reflectance of apple tree canopy were the smallest. The relative errors of all bands were consistent, and its variation trend among the 30 sample apple orchards was also consistent with the measured reflectance, which showed the necessary of pixel unmixing. Moreover, the changes of the reflectance among the sample apple orchards showed similar characteristics when the retrieval method was used for different resolution images. The images with high resolution were more superior, but, because of band limitation, it would be better to integrate the high resolution images with moderate resolution images.

[Remote sensing techniques of apple orchard information extraction based on linear spectral unmixing with measured data].

Taking Qixia City, Shandong Province of China as the research region, and by using pixel unmixing for the TM image at apple flowering stage, the apple orchard information was extracted. Based on the measured spectral end-members, wavelet transform was adopted to improve the linear unmixing model. The improved linear spectral unmixing model, measured end-member based linear spectral unmixing model, and TM image end-member based linear spectral unmixing model were employed to extract the apple orchard information, and the ALOS data were used for accuracy estimation. After the accurate atmospheric and topographic correction, it was feasible to use the measured spectral end-members for pixel unmixing, and the area precision of apple orchard information acquisition was greater than 97%. The regression analysis on the NDVI of abundance image and the average NDVI of ALOS data showed that the R2 was higher than 0.8. Therefore, using wavelet transform to improve the linear spectral unmixing model could improve the unmixing accuracy to a certain degree.