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    20 October 2023, Volume 44 Issue 10
    Effect of Isonitrogen Substitution for Biochar Application on Greenhouse Gas Emissions from Southern No-till Early Rice Fields
    LI Shi, ZHANG Jun-hui, HU Jun-ming, ZHOU Feng-jue, LI Ting-ting, XU Mei-hua, MA Jie-ping, LU Zhan-cai
    2023, 44(10):  863-875.  doi:10.3969/j.issn.1000-6362.2023.10.001
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    Biochar has been recognized as a new exogenous organic substrate and is often used as an important organic resource for carbon reduction because of its stability, adsorption and carbon nutrient richness. The study was conducted in a typical indica rice area of Nanning from 2021 to 2022, against the background of having high early indica rice yields, simultaneous rain and heat, and unique cropping system. In this paper, authors set three treatments: Control treatment (CK): no fertilizer. Inorganic N input (T1, chemical fertilizer) treatment: chemical fertilizer application at conventional fertilizer level, compound fertilizer 800kg·ha−1, urea 260.87kg·ha−1, potassium 193.55kg·ha−1. Inorganic N with organic N (T2, biochar + chemical fertilizer) treatment: biochar 4000kg·ha−1, compound fertilizer 738.67kg·ha−1, urea 146.09kg·ha−1, potassium 34.19kg·ha−1. The cumulative greenhouse gas emissions, emission equivalents, rice yield traits and the effect of isonitrogen substitution of biochar application on greenhouse gas emissions and rice yield in early southern rice fields were analyzed by regular monitoring of soil greenhouse gas emissions in rice fields during the rice reproductive period using a split static box-meteorological chromatography method 5d after rice transplanting, this study provide a basis for optimizing intensive early rice low-carbon cultivation and reduce fertilizer and increase efficiency. The results showed that: (1) biochar can reduce CH4 and CO2 emissions from paddy soils, and reduce the combined emission equivalent by slowing down CH4 emissions. The application of fertilizer with biochar can mitigate the increase of greenhouse gas carbon emissions caused by fertilizer application alone, and its delayed effect of mitigating CO2 emissions is more obvious. In biochar treatment (T2), compared with the chemical fertilizer treatment (T1), the maximum CH4 emission flux in 2021 was reduced by 41.38% and the cumulative emission was reduced by 31.25%, and the maximum emission flux in 2022 was reduced by 50.50% and the cumulative emission was significantly reduced by 50%, and the combined emission equivalents of 2 years were significantly lower than those of the T1 treatment. The maximum CO2 emission flux and cumulative emission in 2021 were reduced by 57.38% and 37.68%, respectively, compared with the T1 treatment, and the corresponding reduction in 2022 was 16.06% and 35.52% compared to the T1 treatment. (2) Biochar can suppress N2O emissions, significantly reduce cumulative emissions, and reduce nitrogen source emission equivalents. Compared to the T1 treatment, the maximum N2O emission flux was reduced by 5.43% and the cumulative emission was significantly reduced by 33.53% in 2021 in T2 treatment; the maximum emission flux was reduced by 73.75% and the cumulative emission was significantly reduced by 54.33% in 2022, and there was no significant change with the CK treatment. (3) Biochar facilitates the optimization of intensive early indica rice cultivation structure and enhances the productivity of early indica rice. After biochar was put into the paddy field for 2 years, the effect of increasing yield became more and more obvious, and the theoretical yield of T2 treatment was 1.02−1.33 times that of T1 treatment, while the actual yield was 1.06−1.32 times that of T1 treatment. Fertilizer with biochar reduced greenhouse gas emissions and increased rice yield in early indica rice fields, which can be used as an optimization model for low-carbon production of intensive early indica rice in the south.
    Effects of Foliar Spraying KH2PO4 on Wheat Grain Setting Characteristics under Late Spring Coldness
    DAI Wen-ci, WANG Peng-na, WENG Ying, HUANG Jin-wei, YU Min, WU Yu, CAI Hong-mei, ZHENG Bao-qiang, LI Jin-cai, CHEN Xiang
    2023, 44(10):  889-902.  doi:10.3969/j.issn.1000-6362.2023.10.003
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    In order to clarify the effect of spraying (potassium dihydrogen phosphate, PDP, KH2PO4) on the grain setting characteristics of wheat under late spring coldness, Yannong 19 (YN19) with strong resistance to reversed late spring coldness and Xinmai 26 (XM26) with weak resistance to reversed late spring coldness were selected as materials. PDP was sprayed on the leaf surface after late spring coldness occurred on March 17−23, 2022 (booting stage). The distribution characteristics of spraying PDP on fertile grain number and grain weight with different spikelet and different grain positions under late spring coldness were compared and analyzed. The results showed that: (1) compared with CK, spraying PDP under late spring coldness increased the total fertile grain numbers of varieties XM26 and YN19. Among them, the total fertile grain numbers at the middle and lower spikelet of XM26 significantly increased by 8.33% and 33.33%, respectively, with no significant effect on the total fertile grain number at the upper spikelets. And the total fertile grain numbers of XM26 at G1 (the first grain position), G2 (the second grain position), G3 (the third grain position) and G4 (the fourth grain position) position increased by 8.11%, 3.13%, 4.35%, and 60.00%, respectively. The total fertile grain numbers at the lower spikelet of YN19 significantly increased by 23.08%, with no significant effect on the total fertile grain numbers at the upper and middle spikelets. The total fertile grain numbers of YN19 at G1, G2 and G3 position increased by 2.70%, 0 and 13.33%, respectively. (2) Compared with CK, spraying PDP under late spring coldness increased the grain weights of varieties XM26 and YN19. Among them, the total grain weights at the middle and lower spikelet of XM26 significantly increased by 18.46% and 46.16%, respectively, with no significant effect on the total grain weights at the upper spikelets. And the total grain weights of XM26 at G1, G2, G3 and G4 position increased by 2.70%, 4.44% and 13.33%, respectively. The total grain weights at the upper and lower spikelet of YN19 significantly increased by 21.70% and 33.63%, with no significant effect on the total grain weights at the middle spikelets. The total grain weights of YN19 at G1, G2 and G3 position increased by 15.97%, 13.12% and 17.55%, respectively. (3) Spraying PDP under late spring coldness mainly alleviates the yield loss by increasing the fertile grain numbers of XM26 with weak resistance to reversed late spring coldness, and increasing grain weight of YN19 with strong resistance to reversed late spring coldness. It was concluded that spraying PDP after the late spring coldness could increase the fertile grain number and grain weight of the lower spikelet and the weaker grain positions to reduce the yield loss.
    Determination of the Suitable Sowing Date of Fresh Maize Along the Yangtze River of Anhui Province
    ZHANG Lin, ZHOU Deng-feng, WU Wen-ming, PENG Chen, JI Xue-qin, YANG Tai-ming, WANG Shi-ji
    2023, 44(10):  903-915.  doi:10.3969/j.issn.1000-6362.2023.10.004
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    A field trial was carried out along the Yangtze river in Anhui province to clarify the relationship between growth, yield of fresh maize and meteorological factors under different sowing dates, which would provide a reference to the suitable sowing date of fresh maize. In the study, the fresh maize cultivar “Caitiannuo 100” was used. The treatments consisted of ten sowing dates: April-1, April-16, May-1, May-16, May-31, June-15, June-30, July-15, July-30, and August-14. The growth period, yield, yield component and production value of fresh maize were analyzed. The results showed that the growth duration was shortened when delaying the sowing date from April-1 to June-15. When the sowing date was from June-15 to July-30, the growth duration was extended. The yield was decreased when delaying the sowing date from April-1 to June-30, and the yield was increased. The mean grain yield of fresh ear in the sowing date from April-1 to May-1 and July-30 was 20026.56kg·ha−1, which was significantly higher than that of other sowing dates (P<0.05). The production value of fresh ear planted in July-30 was 70245.00yuan·ha−1, which was significantly increased by 68.66%−123.50% compared with other sowing dates (P<0.05). When the fresh maize was sowed during May-31 to July-15, the days of high temperature ≥32℃ accounted for 56.25%−60.26% in the whole growth duration of the plant, and the accumulation of temperature ≥32℃ increased by 47.78%-54.46% than that of sowing dates from April-1 to May-1 and July-30, which accelerated the fresh maize growing process, shortened the plant height, declined the matter accumulation, ultimately decreased the yield. The fresh maize could not be harvested with the sowing date of August-14 due to the lower temperature during the grain filling stage. The growth duration of maize was negatively correlated with daily mean temperature before silking. The ranking of the correlation coefficients between meteorological factors and fresh maize yield from high to low were effective accumulated temperature >10℃ before silking, precipitation before silking, daily mean temperature before silking, average daily temperature range before silking, precipitation after silking, effective accumulated temperature >10℃ after silking, and sunshine hours before silking. The effective accumulated temperature >10℃ before silking stage mainly influenced the yield by regulating the kernel number per ear. In conclusion, the fresh maize sowed during April-1 to May-1 or July-30 could be prone to extend growth period, increase matter accumulation, and obtain high yield, while might be in danger in the risk of high temperature stress with the sowing date from May-31 to July-15 along the Yangtze river.
    Effects of Sowing Dates and Furrow Depths on Resource Utilization Efficiency and Yield of Spring Maize
    XIANG Wu-yan, BAI Wei, FENG Liang-shan, CAI Qian, ZHANG Zhe, SUN Zhan-xiang, FENG Chen
    2023, 44(10):  916-928.  doi:10.3969/j.issn.1000-6362.2023.10.005
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    A two-year (2020-2021) field experiment was conducted at the National Agricultural Environmental Station for Agricultural Environment in Fuxin. The experiment was conducted in a completely randomized block design, consisting of five sowing dates with three furrow depths each year. Seeds were sown on April 11 (T1), April 18 (T2), April 25 (T3), May 2 (T4) and May 9 (T5), respectively, in 2020, and were sown on April 18 (T2), April 25 (T3), May 2 (T4), May 9 (T5) and May 16 (T6), respectively, in 2021. The furrow depths including 5cm (D0, convention planting as the control), 10cm (D1) and 20cm (D2), respectively. By measuring above-ground dry matter, grain yield and yield components, soil water content on the sowing and harvesting day, and soil water storage and maize water use efficiency were calculated, so as to explore the rule of dry matter accumulation and allocation of spring maize, and the changes in resource utilization efficiency under the influence of sowing dates and furrow depths. Both contribute to optimize the cultivation technology of spring maize by selecting suitable sowing date and furrow depth in semi-arid region. The results showed that the sowing dates from April 18 to May 2 were beneficial to the accumulation of above-ground dry matter. Compared with the average of other sowing dates, the maturity period was increased by 8.0%, and promoted the allocation of dry matter to ear weight, with an average yield 9.9% higher than other sowing dates. The water use efficiency was significantly improved. The production efficiency of solar radiation, growing degree days, and rainfall increased first and then decreased with the delay of sowing date. The above-ground dry matter and panicle ear weight were D2>D1>D0 in different furrow depth treatments at the maturity stage. The grain yield of D2 and D1 treatments was significantly higher than that of D0 (11.1% on average), and there was a significant difference in water use efficiency in 2020. Considering yield, resource utilization efficiency and variation coefficient of yield, authors concluded that suitable sowing dates(April 25-May 2) and 20cm furrow depth were the most beneficial to high yield and resource utilization efficiency of maize in semi-arid area of western Liaoning.
    Effect of Late Spring Coldness during the Anther Differentiation Period on the Caryopsis Development of Wheat
    WENG Ying, WANG Peng-na, YU Min, DAI Wen-ci, WU Yu, CAI Hong-mei, ZHENG Bao-qiang, LI Jin-cai, CHEN Xiang
    2023, 44(10):  929-942.  doi:10.3969/j.issn.1000-6362.2023.10.006
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    A field pot experiment was conducted using Xinmai26 (XM26) with weak resistance to late spring coldness and Yannong19 (YN19) with strong resistance to late spring coldness. Low temperature (2℃ and −2℃) stress treatment was carried out in intelligent ultra-low temperature light incubator during the anther differentiation period of young wheat spike differentiation, and 10℃ was used as CK control group. The length, width and thickness of the superior and inferior caryopsis of wheat were analyzed by sampling every 7 days after anthesis. At the same time, the microstructures of pericarp, endosperm cells and large and small starch grains were observed by paraffin sectioning technique, so as to explore the microstructures of caryopsis development in wheat under the late spring coldness during the anther differentiation period. The results showed as follows: (1) the length, width and thickness of wheat caryopsis decreased with the increase of cold stress (2℃→−2℃). The length, width and thickness of wheat caryopsis decreased by 1.17%−4.41%, 1.57%−10.22% and 1.42%−9.40%, respectively, at the mature stage. The ratios of length/width, length/thickness and width/thickness of inferior grain caryopsis were higher than that of superior grain caryopsis in all treatments at maturity stage. (2) The degradation rate of early caryopsis pericarp was slowed down. Meanwhile, the development of starch granules in caryopsis endosperm cells of two wheat cultivars was inhibited. (3) The circumference and area of large and small starch grains in wheat superior and inferior caryopsis were decreased by 8.17%−14.66%, 14.08%−17.98%, 0.94%−5.00% and 2.59%−10.03% in endosperm cells of dominant caryopsis at 28 days after anthems. The circumference and area of large and small starch grains decreased by 3.08%−10.31%, 6.59%−8.70%, 3.17%−6.39% and 11.85%−16.17% in endosperm cells of inferior grain caryopsis. The circumference and area of large starch grains decreased more in dominant grain caryopsis, while the circumference and area of small and medium starch grains decreased more in inferior grain caryopsis. In conclusion, late spring coldness during the anther differentiation period can slow down the degradation of pericarp cells of early wheat caryopsis development, inhibit the development of starch grains in endosperm cells, reduce the circumference and area of large and small starch grains in endosperm cells, and thus reduce the length, width and thickness of wheat caryopsis, resulting in the decrease of grain storage capacity of wheat, and ultimately reduce wheat grain weight.
    Application of Deep Learning Technology in Monitoring, Forecasting and Risk Assessment of Agricultural Drought
    HUANG Rui-xi, ZHAO Jun-fang, HUO Zhi-guo, PENG Hui-wen, XIE Hong-fei
    2023, 44(10):  943-952.  doi:10.3969/j.issn.1000-6362.2023.10.007
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    The development of artificial intelligence technology, especially the emergence of deep learning, has promoted new developments of agriculture, and is regarded as a new direction of modern agricultural production. Deep learning has the advantages of strong learning ability, wide coverage, strong adaptability, and great portability. Considering that its development of simulated datasets can solve real-world problems, it is more and more widely used in monitoring, forecasting and risk assessment of agricultural drought. This paper used the method of literature review to summarize the development and application of monitoring, forecasting and risk assessment of agricultural drought, and summarized the principles, advantages and disadvantages of the deep learning model. The practical applications of depth learning model in monitoring, prediction and risk assessment of agricultural drought were systematically summarized. The existing problems of large dataset requirements, long data preprocessing time, narrow predefined category range, and complex remote sensing images were discussed, and the future research directions were prospected. The results showed that in recent years, the technologies of monitoring, prediction and risk assessment of agricultural drought had made important progress. However, due to the nonlinearity of agricultural system and the complexity of disasters, existing technologies were still difficult to meet the needs of actual agricultural production in the new situation in terms of applicable regions, objects and accuracies. The deep learning technology provided a new means for agricultural drought research. However, the deep learning model could not accurately express the specific process and mechanism of crop growth, so coupling of crop growth model with deep learning model could ensure the interpretability of deep learning model. For correcting the prediction sequence, coupling models based on general circulation model and depth learning model could be established to further improve the prediction ability of deep learning model for medium and long-term agricultural drought. Aiming at the problem of limited disaster sample size, strengthening the research on agricultural drought monitoring and evaluation based on migration learning could further improve the precisions in fine monitoring and evaluation of agricultural drought. In view of the fact that the factors affecting agricultural drought formation was characterized by large amount of data, diverse types and nonlinearity, the method of combining deep learning and information fusion was adopted to further improve the accuracies in regional monitoring, prediction and risk assessment of agricultural drought. Therefore, the coupling of deep learning models and crop growth models, agricultural drought prediction by integrating deep learning models and general circulation models, fine monitoring and evaluation of agricultural drought based on deep learning and migration learning, regional monitoring, prediction and risk assessment of agricultural drought based on deep learning and information fusion were considered as the development trends of applicating deep learning technologies in monitoring, prediction and risk assessment of agricultural drought in the future.
    Error Evaluation of Hourly Precipitation Fusion Products during Flood Season in Sichuan and Chongqing
    KUANG Lan, TIAN Mao-ju, LI Qiang, PANG Yue, JI Li, LIU Xiang
    2023, 44(10):  953-963.  doi:10.3969/j.issn.1000-6362.2023.10.008
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    Three sets of precipitation fusion products CMPAS, GSMaP and IMERG in the flood season of 2021, and the hourly precipitation data of 190 national meteorological stations in Sichuan and Chongqing region after quality control were used to test the error analysis of the three sets of products in combination with different terrain intervals and different hourly rainfall intensity in Sichuan and Chongqing region, so as to provide data support for flood season hydrometeorological disaster prevention and reduction. Some results in this study showed that: (1) in terms of the spatial distribution of total rainfall in 2021 flood season, CMPAS products were the closest to the site measured precipitation, followed by GSMaP and IMERG products. (2) According to different topographic areas and different time periods, CMPAS products had the best correlation, hit rate and key success rate, followed by IMERG. The deviation, root mean square error and false positive rate of CMPAS products were the smallest, the false positive rate of GSMaP products was the largest, and the deviation and root mean square error of IMERG products were the largest. The hit rate and critical success rate of all fusion products were the best in August and September, and the correlation, hit rate and critical success rate were the best in 20:00−next 2:00 and 2:00−8:00, while the error and false positive rate were the least. (3) CMPAS was obviously better than IMERG and GSMaP for different hourly rainfall intensity. The correlation, hit rate and critical success rate of CMPAS products in May and September were the best. As the hourly rain intensity increased, the root mean square error of each fusion product increased gradually. The above results indicate that the accuracy of CMPAS products in flood season was obviously better than that of IMERG and GSMaP products in Sichuan and Chongqing, which could provide effective precipitation data supplement for areas lacking ground measured data.
    Report on Agrometeorological Conditions Analysis during Growing Season of Summer Harvest Crops in 2023
    ZHENG Chang-ling, GUO An-hong, ZHAO Xiao-feng, LIU Tao
    2023, 44(10):  964-969.  doi:10.3969/j.issn.1000-6362.2023.10.009
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    Based on the measured agrometeorological data of meteorological observation stations and agrometeorological stations in the main production area of summer grain and oil crops in China from 2022 to 2023, the climate suitable index and disaster index were used to analyze the agrometeorological conditions in the growing season of major summer harvest crops, including winter wheat and rape. The results showed that there were sufficient thermal conditions and sunlight in the main production areas during the winter and rape growing season. At the same time, precipitation and soil moisture conditions are suitable for crop growth and development. Further, agricultural meteorological disasters such as wet damage, late frosts and crop diseases and pests had relatively light effects. It was sunny during most of the mature harvest stage, so the overall progress of the summer harvest was fast. During most of the ripening stage the weather was sunny, so the overall progress of the summer harvest was rapid. However, continuous rainy and heavy precipitation occurred in southern Shaanxi, southern Huanghuai and eastern Jianghan area from May 25th to June 4th, which resulted in delayed wheat harvest, significant decline in wheat quality and local germination mildew. Henan province has been the worst affected in terms of wheat yield and quality. Due to successive droughts in the middle and lower reaches of the Yangtze river and Guizhou, sowing and emergence of rapeseed was delayed significantly and rapeseed seedling condition deteriorated in the later growth. Additionally, the yield of winter wheat and rape was affected by continuous drought in the southern area of Southwest China in winter and spring. Overall, the 2022/2023 winter wheat and rapeseed growing season was slightly less climatically suitable than the previous year, with slightly deviated meteorological conditions.