【Objective】To explore the potential of UAV remote sensing in nitrogen efficiency classification and recognition, a nitrogen efficiency classification method for wheat varieties was constructed, so as to provide the theoretical basis and technical support for nitrogen efficient variety screening.【Method】Six agronomic indicators related to nitrogen efficiency at maturity stage (yield, plant nitrogen accumulation, nitrogen physiological use efficiency, plant dry biomass, total nitrogen uptake of grains, and N harvest index) were used to construct the principal component synthesis value, and K-Means cluster analysis was performed on them. The 121 wheat varieties were divided into three types: high, medium, and low nitrogen efficiency types. A UAV remote sensing platform equipped with a multi-spectral camera was used to obtain remote sensing images of wheat at the jointing, booting and flowering stages, and 34 vegetation indices were extracted to analyze the correlation between vegetation index and nitrogen efficiency comprehensive value. The accuracy of nitrogen efficiency classification models of support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN) classification methods were compared, and the overall classification accuracy (OA) and Kappa coefficient were used to compare the classification and recognition ability of wheat varieties in different growth periods. Three different feature set screening methods(ReliefF algorithm, Boruta algorithm and RF-RFE algorithm) were used to comprehensively evaluate the optimized feature subsets, and an appropriate classification and recognition method for wheat varieties nitrogen efficiency was established.【Result】With the progress of wheat growth stage, the correlation between vegetation index and the comprehensive value of nitrogen efficiency gradually increased, which reached the highest correlation coefficient at flowering stage (r=0.502). The full feature set of vegetation indices was used to classify the nitrogen efficiency of wheat varieties. For the data of single growth stage, SVM model had the best classification accuracy at flowering stage (OA=77.1%, Kappa=0.591), and the worst classification accuracy at jointing stage (OA=65.6%, Kappa=0.406). In general, the classification accuracy of nitrogen efficiency of varieties with multi-growth stage data fusion was higher than that of single growth stage, among which SVM model with jointing stage + booting stage + flowering stage had the best classification accuracy (OA=80.6%, Kappa=0.669). In order to reduce the number of feature set variables in multi-growth period data fusion, the feature optimization effects of RF-RFE, Boruta and ReliefF algorithms were compared and analyzed. The optimal feature subset based on RF-RFE algorithm had the highest classification accuracy, and its OA and Kappa coefficients were 4.0% and 10.1% higher than those of the full feature set classification model, respectively. Among them, the data fusion of three growth stages had the best classification accuracy (OA=85.4%, Kappa=0.749).【Conclusion】The nitrogen efficiency evaluation method with six nitrogen efficiency indexes - principal component analysis -K-Means were established in this study. The RF-RFE algorithm effectively optimized the number of characteristic subsets of the multi-growth period combination, and obtained high classification accuracy. A nitrogen efficiency classification model of wheat varieties based on the fusion of multi-growth period combination and RF-RFE-SVM technology was established, which provided the theoretical basis and technical support for the rapid and accurate classification and identification of wheat varieties with nitrogen efficiency.

【Objective】To evaluate the drought resistance of synthetic wheat germplasm based on multi-source images collected by unmanned aerial vehicle (UAV) and yield data, explore high-throughput indices for drought resistance evaluation, and identify synthetic wheat germplasm resources with drought resistance. This provides technical support and germplasm materials for accelerating the expansion of drought-resistant genetic resources for wheat and enhancing the level of breeding for dryland wheat.【Method】Eighty synthetic wheat germplasm and the control variety Xin Chun 37 were used as plant materials, which were sown in the field and treated with a water regime of drought stress and irrigation. Multi-source images of test materials during filling stage were collected by multi-spectral and thermal infrared cameras equipped with unmanned aerial vehicle, and the spectral index of each test material was extracted by threshold segmentation. The analyses of Pearson’s correlation and principal component were performed to identify drought resistance-related spectral indices, and the drought resistance of each synthetic wheat germplasm was determined by single index and comprehensive evaluation methods. 【Result】The drought resistance coefficients of 19 spectral indices of 80 synthetic wheat germplasm were calculated based on multisource imagery data obtained from unmanned aerial vehicles. The correlation analysis between the spectral indices and the yield-based drought index (DRI) showed that among the drought resistance coefficients of the 19 spectral indices, OSAVI exhibited the highest correlation with the drought index, while NDVI, CI_re, and NDRE demonstrated relatively strong associations with the drought index. However, the different drought indices showed a high correlation, resulting in redundant information. The drought resistance coefficients of the 19 spectral indices were transformed into three independent comprehensive indicators through principal component analysis, with contribution rates of 59.6%, 12.0% and 9.6%, respectively. The comprehensive drought resistance index (D) for each synthetic wheat germplasm were calculated by aggregating the three independent comprehensive indicators using the weighted membership function method. 6 and 5 synthetic wheat germplasms with strong drought resistance were identified based on DRI and D, respectively. Among them, 2 germplasms (SW004 and SW009) with high drought resistance were detected based on both DRI and D. Furthermore, the drought resistance of the 80 synthetic wheat germplasms was graded based on the drought resistance coefficient of OSAVI, and the grading results were found to be consistent with that based on the D value. Among the six strongly drought-resistant germplasms identified based on the drought resistance coefficient of OSAVI, five of them were also classified as strongly drought-resistant germplasms based on comprehensive drought resistance evaluation.【Conclusion】The spectral indices NDVI, OSAVI, CI_re and NDRE extracted from UAV-based multi-source images, as well as the drought resistance comprehensive evaluation value can be used to assist in the identification of drought resistance of wheat germplasm.

【Objective】Drought is one of the most destructive environmental stresses limiting wheat production. The novel germplasm with excellent drought tolerance as well as their candidate loci were identified and characterized to enrich the genetic basis of drought tolerance and lay a material foundation for wheat genetic improvement in China. 【Method】In this study, the drought tolerance of 198 wheat accessions introduced from International Dry Area Agriculture Research (ICARDA) were investigated at seedling stage through hydroponic method with PEG6000 simulating drought. Drought tolerance index (DTI) was calculated using the shoot fresh weight, root fresh weight, total biomass and root-shoot ratio, respectively. Genome-wide association analysis was performed using 660K SNP array genotyping to obtain the SNP loci and chromosome regions associating with drought tolerance index. Combined with the expression patterns in root and other tissues, the potential candidate genes were identified, and then they were further verified by qRT-PCR approach with the most drought-tolerant accession IR214 and the most drought-sensitive accession IR36 as materials. Finally, the excellent haplotypes of key candidate genes were analyzed. 【Result】Compared to normal control condition, the growth and development of wheat were significantly impaired under drought treatment. There were also significant phenotypic variations among different accessions with all of the four traits displayed normal distribution. The coefficient of variation ranged from 0.363 to 0.760 with genetic diversity from 0.310 to 0.400. Using the weighted membership function value (D value), the drought tolerance of these accessions was evaluated. Results showed that accession IR214 had the highest D value with 0.851, followed by IR92, IR213, IR235, and IR218, which could be considered as the novel excellent drought-tolerance germplasm. Furthermore, through genome-wide association study (GWAS) analysis, a total of 102 loci were significantly associated with the DTI values based on these four traits, with the phenotypic variation explained value (PVE) from 1.07% to 38.70%, of which 60 loci were associated with above-ground fresh weight, 1 locus associated with underground fresh weight, 36 loci associated with biomass and the remaining 5 loci associated with root-shoot ratio. Then, 31 candidate genes were predicated based on genomic annotation information and LD block. Combined with the expression patterns of them in roots and other tissues, 4 candidates displaying differential expression between CK and drought conditions were obtained. Finally, the expression levels of these 4 candidates were further verified by qRT-PCR method with the most drought- tolerant accession IR214 and the most drought-sensitive accession IR36 as materials to obtain two key candidates associating with drought tolerance. Additionally, their haplotype effects were investigated. It was found that the different genotypes of AX-86174509 locus in TraesCS6A02G048600 gene showed significant differences in drought tolerance, which might be considered as a causal locus.【Conclusion】Totally, 102 loci and 2 key candidate genes (TraesCS5B02G053500 and TraesCS6A02G048600) underlying drought tolerance at seedling stage were detected in ICARDA-introduced wheat, and AX-86174509 in TraesCS6A02G048600 was a potential functional locus.

【Objective】Drought is a major environmental factor limiting global wheat production, and breeding drought-tolerant varieties is a key challenge faced by wheat breeders worldwide. Spring wheat, which has a short growth period, plays a vital role for national food security and planting structure, therefore, it is of great importance to identify and select drought tolerance of spring wheat varieties for breeding of high-yielding and drought-tolerant wheat.【Method】In this study, 244 spring wheat varieties (lines) from 10 different regions were used to assess the drought tolerance of spring wheat varieties during the seedling stage, this study used the controlled water content method to impose drought stress during the seedling stage, 5 seedlings with uniform and consistent growth were selected during the trefoil stage. Thirteen seedling stage indicators including maximum root length (MRL), first leaf length (FLL), first leaf width (FLW), coleoptile length (CL), shoot fresh weight (SFW) and root fresh weight (RFW) were measured. Comprehensive evaluation of drought resistance of various spring wheat varieties (lines) was conducted through methods such as using descriptive statistics, membership function, principal component analysis, cluster analysis, and correlation analysis. 【Result】The drought tolerance of spring wheat varieties (lines) exhibits a large variation. The coefficient of variation of the measured traits under drought treatment conditions ranges from 2.1% to 32.9%, while the coefficient of variation of the control group ranges from 1.0% to 29.3%. Compared with the control, the coleoptile length, root dry weight, fresh weight root to shoot ratio, and dry weight root to shoot ratio under drought treatment were all greater than those under the control treatment. The original 13 indexes were summarized into 5 principal components, and the contribution rate reached 79.56%, and the D value of the comprehensive drought resistance coefficient was calculated according to the characteristic vector of each principal component and the drought resistance coefficient of each trait index, then the D value was clustered and analyzed, which could be divided into 5 subgroups. Therefore, the root biomass (underground fresh weight and dry weight) was screened as an effective comprehensive index for the identification of drought resistance at the seedling stage. We conducted correlation analysis between the seedling stage drought index and the agronomic traits of maturity stage showed that the coleoptile length, first leaf length was significantly positively correlated with flag length, plant height, spike length, the number of spike and grain length. Additionally, and the seedling biomass was significantly positively correlated with thousand-grain weight.【Conclusion】Twenty-two highly drought-tolerant varieties were screened, and root biomass (both fresh and dry weight of the underground part) was identified as an effective comprehensive indicator for evaluating seedling stage drought tolerance.

Wheat is the most important cereal crop, and drought is the most significant abiotic stress factor that severely affects wheat growth and development. Plant root system, as a primary organ for crops to acquire water and nutrients, directly determines the efficiency of soil water utilization. In recent years, increasing evidence has shown that plant root system architecture (RSA) plays an important role in plant tolerance to drought stress. This review summarizes the current research progress on the regulation of wheat drought tolerance determined by RSA. First, we present how root tropism especially root gravitropism shapes the RSA, summarize the relevant genes and molecular regulatory mechanism involved in root gravitropic growth, and explain how the root tropism-regulated RSA is implicated in wheat adaptation to drought stress. In addition to root tropic growth, the root development also participates in the RSA formation and the plant adaptability to drought stress. Therefore, this review further summarizes how wheat regulates root development to alter its root system morphology (including increasing root length, modifying lateral root number and root hair density, etc.), thereby enhancing its water acqusition from the soil and its adaption to drought environment. The identified genes involved in wheat root development under drought stress conditions are also systematically summarized. Furthermore, as the underground part of plants, the revelation of RSA has always been a challenging task, which hinders our understanding of the relationship between RSA and plant drought tolerance. Therefore, this review also summarized the available techniques used to analyze the RSA at two- and three-dimension levels. These techniques can measure and analyze wheat root length, density, growth direction, and morphology parameters, laying technical support for an insightful understanding of the relationship between wheat RSA and drought resistance. Finally, we discuss the prospect of the improvement of RSA in breeding wheat drought-resistant varieties, as well as provide an outlook for how to identify genes regulating wheat RSA and pinpoint their regulatory mechanism. In summary, the relationship between wheat RSA and drought resistant is closely associated. The continuous development of sequencing techniques, along with the deepening research on the regulatory mechanism of wheat RSA, will provide new means and strategies for the further breeding of drought-tolerance wheat varieties.

为减少粮食因破碎而导致的损耗浪费，探索玉米颗粒的抗破碎能力，该研究利用准静态压缩试验共获得了920组玉米粒的力学数据，并通过韦伯分布拟合对玉米粒破碎力进行了分析。试验对比压缩方位及压缩速率对玉米粒破碎力的影响，确定准静态压缩的试验条件，在此基础上探索玉米含水率、粒径、轴比对玉米粒破碎性质的影响。结果表明：沿玉米厚度方向压缩可获得玉米粒的最大破碎力；压缩速率小于0.10 s−1时，压缩速率对玉米粒破碎力分布无影响。另外，玉米粒的含水率、粒径、轴比均影响其破碎力分布。含水率14.72%的玉米粒破碎力分布更为集中；小粒径玉米粒更容易破碎，粒径小于7 mm时玉米粒破碎率达100%；玉米粒破碎率和破碎力均与轴比呈反比，表明饱满圆润的玉米颗粒更容易发生破碎。该试验为玉米在储运、加工过程中的降碎降损提供了可靠的数据支撑。

植物蛋白纤维由于其独特的结构和极高的纵横比可作为良好的疏水性生物活性物质的递送载体。为了提高玉米醇溶蛋白在酸热诱导下的纤维化程度，该研究采用低温等离子体技术辅助完成玉米醇溶蛋白自组装纤维化，探究诱导过程中各因素对玉米醇溶蛋白纤维化程度的影响机制，并通过单因素和响应面试验获得最优纤维化工艺。硫黄素T（ThT）荧光强度结果显示，采用等离子体辅助酸热诱导可以有效提高玉米醇溶蛋白的纤维化程度。通过单因素和响应面优化试验获得了制备纤维化玉米醇溶蛋白的优化工艺为等离子体处理功率64 W，处理时间61 s，加热时间为10 h，加热温度70 ℃，蛋白质量浓度30 mg/mL。在此条件下纤维化玉米醇溶蛋白ThT荧光强度可达2 272±23，显著高于未经等离子体处理的纤维化玉米醇溶蛋白（1 239±19）（P＜0.05）。对傅里叶变换红外光谱中酰胺I 区结果分析表明，等离子体处理使玉米醇溶白中β-折叠结构增加，α-螺旋结构减少。透射电子显微镜观察到玉米醇溶蛋白经过纤维化后颗粒粒径明显下降，其纤维结构是由球状蛋白颗粒沿水平方向线性聚集而成，采用等离子体辅助可诱导形成更多的玉米醇溶蛋白纤维体结构。研究结果为疏水性植物蛋白实现高效自组装纤维化提供参考。

烟叶的部位信息是进行烟叶分级的重要参考信息，准确识别烟叶部位对实现烟叶智能分级具有重要意义。在实际的烟叶智能分级应用中，为了提高分级效率，需要对多片烟叶等级进行同步识别。受现行上料方式的限制，同步识别的多片烟叶间往往存在局部遮挡的问题，给烟叶的目标检测和部位识别带来挑战。该研究提出一种基于改进Cascade Mask R-CNN，融合通道、非局部和空间注意力机制（channel-nonlocal-space attation），并引入柔性极大值抑制检测框交并操作（soft non-max-suppression）与斯库拉交并比损失函数（SIoU）的目标检测与识别模型（CSS-Cascade Mask R-CNN）。该模型对Cascade Mask R-CNN进行了三方面的改进：一是在其骨干网络Resent101上同时引入通道、非局部、空间3种注意力机制，使网络更加关注未被遮挡且部位特征明显区域的显著度；二是将Cascade Mask R-CNN中的损失函数SmoothL1Loss替换为SIoU损失函数，将预测框与真实框之间的方向差异引入到模型训练中提高模型检测精度；三是在筛选候选框时将常规的非极大抑制（non-max-suppression）替换为柔性非极大抑制，以避免删除候选框造成信息丢失。试验结果表明，利用提出的模型对有遮挡多片烟叶进行检测和部位识别，检测框平均准确率均值（bbox_mAP50）达到了80.2%，与改进前的Cascade Mask R-CNN模型相比提高了7.5个百分点。提出的模型与多个主流的目标检测模型（YOLO VX、YOLO V3、YOLO V5、Mask R-CNN、Cascade R-CNN）相比，也分别高出7.1、10.2、5.8、9.2、8.4个百分点，尤其是对较难区分的下部烟叶优势明显，因此研究结果可以为有遮挡多片烟叶部位的检测识别提供参考。

为改善挤压大米淀粉的功能特性，以米粉（rice, R）为主要原料，探究了不同槲皮素（quercetin, Q）添加量（0 ～ 10%）在挤压场下对米粉中淀粉的水溶性、吸水性、糊化特性等功能特性的影响。在此基础上，借助扫描电子显微镜（scanning electron microscopy）、X-射线衍射、红外光谱、及紫外可见光分光光度计揭示了Q在挤压场下对淀粉结构的演变规律。试验结果表明：当Q添加量为4%时，样品的吸水指数，碘结合能力均达到了最大值，且自由水弛豫时间提前；挤压体系中Q与淀粉通过氢键结合，颗粒结构变得更加立体、紧凑。与挤压米粉相比，槲皮素的添加延缓了淀粉的回生且提高了淀粉的热稳定性。根据以上结果可知，挤压体系中Q与大米淀粉复合，促进了淀粉分子链重排，进而改变淀粉的结构及功能特性，该研究可为开发抗回生的挤压大米淀粉基产品提供理论依据。

黄河中上游地区生态环境脆弱，空间发展问题突出，探索该区域土地使用结构和布局优化配置是实现黄河流域生态保护和高质量发展的有效途径。该研究以黄河中上游地区为研究对象，基于该区域土地使用、社会经济等数据，运用多目标规划（multi-objective programming, MOP）和PLUS模型模拟了惯性发展、生态保护、经济优先和生态-经济均衡4种情景下研究区未来土地格局和变化趋势，并在平衡生态与经济的目标下提出最优土地使用结构和布局方案。结果表明：1）4种情景下，土地使用比例结构存在较大差异；2）均衡情景下的区域土地使用结构和空间布局方案为最优，其综合效益值最高且达到19481.01亿元，与生态保护情景相比其经济效益（12223.88亿元）增长了4.03%，与经济优先情景相比其生态价值（77257.12亿元）增长了2.32%；3）经济优先情景下综合效益值为20273.96亿元，是4种情景下最高的。研究可为黄河中上游区域未来土地使用规划编制和土地可持续利用规划提供依据。

科学确定高标准农田改造提升的重点区域是切实发挥高标准农田建设成效、提升粮食生产能力的关键。该研究以山东省乐陵市为研究区，运用层次分析法和TOPSIS法构建考虑农田基础设施、耕地地力质量和水资源利用状况的高标准农田改造提升迫切性评价体系，并基于维度间的耦合协调度及其空间特征划定改造提升项目区。结果表明：1）乐陵市已建高标准农田占耕地面积的87.93%，西南和东部地区建设基础较好，南部和中部薄弱；高等地力农田面积较少，分布于中南地区和东北地区；水资源利用状况总体呈现“中部高、北部和南部低”的特征。2）农田基础设施、耕地地力质量和水资源利用状况三个维度间的耦合协调度指数为0.41～0.85，高值聚集分布于西南部、东部和东北部，低值聚集分布于南部和西北部，中值交叉分布于中西部和中南部地区。3）基于耦合协调度指数及其空间特征遴选出12个高标准农田改造提升项目区，根据指数分级结果从低到高确立为近期（8633.23 hm2）、中期（11004.64 hm2）、远期（9102.62 hm2）建设项目。结合各项目区立地条件和高障碍度、高频率障碍因子，建议围绕资金整合、水源保障、设施配套、地力提升、结构改良等方面分类推进。该方法对于高标准农田改造提升区域选择以及重点建设方向确定具有一定借鉴价值。

针对天然生物质材料应用于海水淡化领域，蒸发效率较低、材料容易降解等问题，采用多巴胺对天然玉米芯进行改性处理，以改性玉米芯为基底，在其表面包覆炭黑-纤维素薄膜，制备了一种集光热转换、输水、隔热于一体的太阳能界面蒸发体。对改性玉米芯蒸发体的光学吸收性能、输水性能、接触角进行表征，并搭建了室内蒸发试验和户外蒸发试验系统，测试了改性玉米芯的蒸发性能，与天然玉米芯相比，改性玉米芯蒸发体的蒸发速率相对未改性的提升了约10.4%。对改性玉米芯蒸发体进行了30次循环试验，蒸发体均保持稳定的蒸发速率，整个循环测试中蒸发速率波动不超过1%。并且，长期工作后，蒸发体表面没有盐分沉积，没有出现材料软化、降解现象。改性玉米芯蒸发体在海水环境中能够保持良好、稳定的蒸发性能，且能够有效降低海水中的Na+、K+、Mg2+、Ca2+等离子浓度，达到世界卫生组织所规定的饮用标准中的相应限值。改性玉米芯蒸发体的制备方法简单、成本低廉、蒸发性能稳定，为扩展生物质材料在海水淡化领域的应用提供了有效途径。

针对目前LED表面发热量较大，局部温度过高，而导致其使用寿命减少的问题，该研究以平板微热管为核心传热元件，与锯齿形翅片结合，设计了一种U型平板微热管散热器。采用试验和仿真模拟相结合的方法，对不同风速、翅片结构、翅高及翅间距等关键影响因素进行分析。结果表明：通过对比分析U型平板微热管在两种室外工况下各测点试验值和模拟值，散热稳定后温度的最大误差分别为4.2%和6.7%，验证了模型的可靠性。风速分别为0.5 m/s和3.0 m/s时，锯齿型翅片都具有良好的散热性能。当风速为3.0 m/s时，锯齿型翅片、W型翅片、直翅片散热器稳定后热源温度分别为34.3、35.5和39.1 ℃。为找到最佳工况和结构，进行了正交分析，当室外风速为3.5 m/s，锯齿型翅片翅高为12 mm，翅间距为8 mm时，U型热管具有较佳的散热性能。研究结果可为LED散热系统的设计提供数据参考和设计思路，拓宽LED光源的应用范围。

为了探究不同光质和光质配比对香菇菌丝生长及转色期的影响，该研究采用9种LED光质处理，以香菇‘L808’为试材，测定了香菇菌丝生长及转色期的生长势、转色特点及5种胞外酶活性，并采用线性回归和主成分分析方法对各指标进行评价。结果表明：在菌丝生长期，与黑暗处理（CK1）相比，红光处理下菌丝平均生长速率显著提高12.13%（P＜0.05），羧甲基纤维素酶（carboxymethylcellulase，CMC酶）活性平均增加66.81%，而红蓝光比为3︰7时，菌丝平均生长速率显著降低2.62%（P＜0.05），CMC酶活性平均降低10.46%。在菌丝转色期，与白光处理（CK2）相比，红蓝光7︰3处理第54天时菌丝完成转色，漆酶活性平均增加19.21%，而此时红光和黄光处理下的菌丝未转色，漆酶活性平均降低9.50%。菌丝生长期CMC酶活性与木聚糖酶活性、淀粉酶活性与漆酶和多酚氧化酶活性均呈正相关。菌丝转色期CMC酶活性与木聚糖酶活性、淀粉酶活性、漆酶活性呈正相关，淀粉酶活性与漆酶活性、多酚氧化酶活性呈正相关。综上所述，红光和红蓝光7︰3分别是菌丝生长期和转色期的适宜光质。该研究结果可为香菇生长的LED光质选择以及香菇工厂化栽培下的光环境控制提供理论依据。

为研究奶牛舍采用扰流风机降温对奶牛泌乳性能和免疫功能的影响，该研究选择结构和饲养管理相同的两栋泌乳牛舍，检测安装风机（风机舍）和不安装风机（对照舍）对不同时期奶牛泌乳性能、淋巴细胞凋亡率、血液理化指标及免疫相关基因mRNA表达的影响，并分析奶牛泌乳性能、免疫性能指标与等温指数（equivalent temperature index for cattle，ETIC）之间的相关性。结果表明：1）安装风机改善了舍内温热环境，整个试验期风机舍的平均ETIC较对照舍降低了3.52 ℃，有效缓解了奶牛的热应激。2）风机舍的产奶量和4%标准乳在试验中、后期均显著高于对照舍（P<0.05），且风机舍的乳脂率较对照舍也表现出显著性提高（P<0.05）。3）安装风机改善了热应激条件下奶牛的免疫功能。与对照舍相比，风机舍奶牛血液中淋巴细胞数量在试验中、后期显著增加（P<0.05），并降低了淋巴细胞的早期凋亡率（P<0.05），淋巴细胞中促凋亡因子Bax的mRNA表达量及其血清浓度在试验后期均表现出显著性降低（P<0.05），抗凋亡因子Bcl-xl的mRNA表达量（P<0.01）及其血清浓度（P<0.10）在试验中、后期表现出增加趋势。此外，风机舍的血清白细胞介素-12（Interleukin-12, IL-12）和免疫球蛋白G（Immunoglobulin G, IgG）浓度较对照舍也表现出显著性增加（P<0.05）。4）从各项指标之间的相关分析得出，乳蛋白率、淋巴细胞数量与ETIC均呈显著负相关关系（P<0.05），淋巴细胞BAK mRNA表达、血清IL-6浓度与ETIC呈显著正相关关系（P<0.05）。 可见，安装扰流风机可改善舍内温热环境，有效缓解夏季奶牛的热应激，提高奶牛生产性能和免疫功能。

为探究未经脱抗预处理的抗生素菌渣作为单一底物厌氧无害化处理的可行性，该研究以新鲜的红霉素菌渣（erythromycin fermentation residue，EFR）及其上清液为原料，在常温（20 ℃）、中温（35 ℃）和高温（55 ℃）条件下开展产气潜能及其动力学研究。研究结果表明：中温条件下，EFR获得最高的累积甲烷产量，为460 mL/g，比常温和高温时分别提高了163%和55.5%.通过一级动力学模型可以看出，EFR的产甲烷过程呈现明显的两阶段特性，其中高温时的产甲烷速率（ k1 =0.1 422 d−1）显著高于常温（k1 =0.0 429 d−1, P<0.05）和中温（k1 =0.0 363 d−1, P<0.05）。物料衡算分析显示，随着发酵温度的升高，EFR的水解转化率逐级提高，高温时最高为87%，表明高温条件下菌渣中残留的红霉素对水解菌基本未产生抑制作用。未经脱抗处理的EFR可直接作为厌氧发酵的原料，为菌渣的减量化和资源化处理提供了新的思路。

为掌握长江干流沿江地区土壤重金属状况，开展土壤表层样品采集和重金属空间分布研究，使用PMF（positive matrix factorization）模型解析土壤重金属来源，并选取地累积和潜在生态风险等方法，评估重金属的污染状况和生态风险。结果表明：1）土壤重金属的积累程度不同，As、Cd和Cu的超标率高，污染明显。Cd和Cu的变异系数高于1.0，分布不匀，受某些污染源的影响显著。2）各重金属含量呈现条带状的空间格局，在多个地区出现高值，土壤环境质量受到人类活动的负面影响。3）土壤重金属积累主要来源于自然、工业排放、交通运输和农业生产，贡献率分别为36.65%、28.48%、20.07%和14.80%。其中Cd与工业活动有关，Pb和Zn来自交通排放，Cr和Ni与自然源密切相关，As和Cu来源于农业生产。4）Cd的污染程度最高，81.88%的点位达到轻度污染。40%以上的点位受到As、Cu、Ni和Pb污染。75%以上点位的Cr和Zn含量较低，污染程度不高。单项生态风险指数的均值从大到小依次为：Cd、As、Ni、Cu、Pb、Zn、Cr。综合生态风险指数均值为63.17，处于轻微风险水平。该研究作为土壤生态调查的核心，可为土壤环境管理和重金属污染修复提供科学依据。

在香菇栽培中，需要评估其生长发育状态，以便调控栽培环境和采取适当的栽培措施。针对香菇生育期子实体外观特征变化不显著，机器自动采收时部分成熟期香菇子实体易误检和漏检的问题，该研究提出了一种基于改进YOLOv5的香菇子实体生育期识别方法。首先替换YOLOv5模型中上采样模块，采用一种包含上采样预测模块和特征重组模块的轻量级上采样模块；其次在YOLOv5l模型中添加小目标检测层，增加模型对香菇子实体生育期特征信息的提取，提高模型区分香菇生育期和识别小香菇的能力。试验结果表明，改进的 YOLOv5l 模型具有较好的检测能力，平均帧率为 45.25 帧/s，平均精确度均值为92.70%，与SSD、Faster-RCNN、Mushroom-YOLO和YOLOv5相比平均精确度均值分别提升22.6、28.38、6.8和2.5个百分点。该研究方法能够满足对香菇子实体不同生育期识别的精度与速度要求，为香菇子实体生育期识别提供了一种方法参考。

针对笼养鸡舍环境下光照强度弱、作业通道内狭小导致机器人巡检时通道中心线检测困难的问题，该研究利用3D激光雷达对鸡舍通道中心线进行获取。首先通过机器人搭载的3D激光雷达对鸡舍作业通道信息进行采集，利用直通滤波、地面点滤波、体素滤波、统计滤波和平面投影对获取的3D激光雷达点云数据进行预处理，获取XOY平面上的点云数据。通过改变K-means聚类初始点选择方式和聚类函数对预处理后的点云数据进行数据分类。利用改进RANSAC算法对分类后的数据进行处理，提取通道中心线。试验结果表明该研究提出的改进K-means聚类算法平均耗时6.98 ms，相较于传统的K-means聚类算法平均耗时减少了29.40 ms，准确率提高了82.41%。该研究提出的改进RANSAC算法中心线提取准确率为93.66%、平均误差角为0.89°、平均耗时为3.94 ms，比LSM算法得到的平均误差角高0.14°，平均耗时减少6.15 ms。表明该研究提出的鸡舍通道中心线检测方法基本满足笼养鸡舍环境实时自主导航的需求，为巡检机器人在鸡舍作业通道内进行激光雷达导航提供了技术支撑。

饲料作为奶牛重要的营养来源，预测饲料消耗状态对于保障奶牛的健康和提高生产管理效率具有重要意义。然而，由于饲料消耗状态数据呈现出非线性和非平稳的特点，导致预测精度较低。为解决此问题，该研究基于经验模态分解（empirical mode decomposition，EMD）和长短期记忆网络（long short-term memory，LSTM），提出了组合改进的自适应噪声完全集成经验模态分解（improved complete ensemble empirical mode decomposition with adaptive noise，ICEEMDAN）、随机森林（random forest，RF）与改进的LSTM（improved LSTM，ILSTM）的模型，即ICEEMDAN-RF-ILSTM，来预测饲料消耗状态。其中，ILSTM是对LSTM的改进，其通过调整遗忘门的输出值范围以增强模型的特征学习能力。首先，使用ICEEMDAN对饲料消耗状态数据进行分解，得到多个相对平稳的分量。其次，考虑到每个分量具有不同的特性，采用不同的方法来建模不同的分量，以进一步提升预测效果。具体而言，为了提升模型的精度以及泛化能力，使用RF建模频率最高的分量；同时，使用ILSTM建模其余分量，以捕获序列数据中的长期依赖性。最后，将所有分量的预测结果相加得到最终的预测结果。基于自建数据集的试验结果表明，ICEEMDAN-RF-ILSTM对于饲料消耗状态预测具有较高的准确度，其决定系数R2、平均绝对百分比误差MAPE与均方根误差RMSE指标分别为0.993、2.576%和0.596%，表明其能有效预测饲料消耗状态，同时其性能优于ICEEMDAN-LSTM模型。该研究为评估饲料消耗状态提供了可行的方法，为制定调度决策提供了科学的技术支持，并为牧业智能化建设提供借鉴。

The aims were to evaluate the eating quality difference of different waxy corn varieties, and screen the germplasm of waxy corn with excellent eating quality. In this study, 19 fresh waxy corn varieties from different sources were used as experimental materials, 17 eating quality traits included peel traits, grain water content, soluble sugar content, starch viscosity RVA characteristic values, and starch content were determined in 19 fresh waxy corn varieties. Variation analysis, correlation analysis, and principal component analysis were used to establish a comprehensive evaluation model for eating quality of waxy corn and screen the waxy corn varieties with excellent eating quality. The results showed that starch viscosity RVE characteristic values, such as peak viscosity, final viscosity, setback viscosity, and consistence viscosity among 19 waxy corn varieties had large coefficient of variation, significant correlation with each other, and occupied a high load in principal component 1, which could better reflect the difference of eating quality of waxy corn. The comprehensive score values of 19 waxy corn varieties showed that ‘YN811’ ‘291’ and ‘Jingnuo 832’ had higher principal component comprehensive scores and taste scores. In conclusion, the starch viscosity RVE characteristic values, such as peak viscosity, final viscosity, setback viscosity, and consistence viscosity, are the key evaluation indexes for identifying the eating quality of waxy corn. ‘YN811’ ‘291’ and ‘Jingnuo 832’ are the high-quality waxy corn varieties with better eating quality.

为改善在农田环境下无人机图像计算速度和效率，该研究提出了一种农田环境下无人机图像并行拼接识别算法。利用倒二叉树并行拼接识别算法，通过提取图像拼接中的变换矩阵，实现拼接识别同时进行。根据边缘设备的CPU核心数和图像数量自动将图像拼接识别任务划分为多个子进程，并分配到不同核心上执行，以提高在农田环境下的计算效率。试验结果表明：相同试验环境和数据集条件下，倒二叉树并行拼接算法的拼接耗时相较于商业软件平均减少了60%～90%左右；在农田环境下，倒二叉树并行拼接识别相较于串行拼接识别的耗时减少了70%，图像识别的平均像素交并比提升了10.17个百分点，说明在农田环境下采用多线程倒二叉树并行算法可以更好地利用农田环境下边缘设备的计算资源，大幅提升无人机图像的拼接和识别的速度，为无人机的快速实时监测提供技术支撑。

The cold acclimation can improve the cold tolerance of insect significantly. This article reviewed the methods of insect cold acclimation and the biological indicators for cold tolerance, the biotic factors (insect development stage, gender and diapause) and abiotic factors (temperature, photoperiod, humidity, etc.) that affect the cold acclimation of insect were analyzed. Then, the impact of cold acclimation on insect in terms of growth and development, reproductive capacity and offspring was clarified. Furthermore, the mechanism of improving insect cold tolerance through cold acclimation was explored from the perspectives of cold resistance related proteins and metabolic regulation. It is expected to provide reference for the deep study of cold acclimation and cold storage techniques of insects, in order to promote the utilization of natural enemies and pest control.

目标检测与分割是实现黄花菜智能化采摘的关键技术，原始目标检测算法容易出现漏检、误检等问题，无法满足自然环境下生长的黄花菜采摘要求。该研究提出一种基于改进YOLOv7-seg的黄花菜目标检测与实例分割识别算法模型（YOLO-Daylily）。通过在YOLOv7-seg骨干网络（backbone）中引入CBAM（convolutional block attention module）注意力机制模块，降低背景等干扰因素的影响；在ELAN（efficient layer aggregation networks）模块中采用PConv（partial convolution）替换原有的3×3卷积层，减少冗余计算和内存访问，提升对目标黄花菜特征提取的能力。颈部网络（neck）采用坐标卷积（CoordConv）替换PA-FPN（path aggregation-feature pyramid networks）中1×1卷积层，增强模型对位置的感知，提高掩膜（mask）鲁棒性。在改进的PA-FPN结构中采用残差连接方法将浅层特征图几何信息与深层特征图语义信息特征相结合，提高模型对目标黄花菜的检测分割性能。消融试验表明：改进后的算法检测准确率、召回率和平均精度分别达到92%、86.5%、93%，相比YOLOv7-seg基线算法分别提升2.5、2.3、2.7个百分点；分割准确率、召回率和平均精度分别达到92%、86.7%、93.5%，比基线算法分别提升0.2、3.5、3个百分点。与Mask R-CNN、SOLOv2、YOLOV5-seg、YOLOv5x-seg算法相比，平均精度分别提升8.4、12.7、4.8、5.4个百分点。改进后的模型减少了漏检、误检等情况，对目标定位更加精准，为后续黄花菜智能化采摘实际应用提供理论支持。

This study focuses on discovering the antimicrobial fungal resources from forest litter fungi, screening out and identifying the fungal strains with antimicrobial activities, and isolating and purifying their antimicrobial compounds. The forest litter from the Greater Hinggan Mountains was selected as test materials, then the fungi were isolated by particle separation method, the taxonomic data were measured by gene sequence comparison, the antibacterial activity was measured by well diffusion method, the monomeric compounds were isolated by column chromatography, and the chemical structure was determined by spectral analysis. Fungal strain SGSF801 was isolated and identified as a new strain of Neocucurbitaria salicis-albae by multiple sequence analysis. The results of the antimicrobial assay showed that the rice fermentation products had strong antimicrobial activities against plant pathogens Ralstonia solanacearum, Pseudomonas syringae and Rhizoctonia solani. The product of fungal rice fermentation was isolated and purified to obtain a monomeric compound, which was identified as Cercosporamide by ¹H-NMR and ¹³C-NMR, and its molecular formula was C₁₆H₁₃NO₇. Its MIC values were 31.25-62.5 μg/mL for Ralstonia solanacearum and 125-250 μg/mL for Pseudomonas syringae. In this study, Cercosporamide was isolated from fungal genus Neocucurbitaria for the first time, and it was found to have antibacterial activities against plant pathogens, which provided a basis for further utilization of litter fungi resources.

The objectives of this study were to clarify the multi locus sequence typing (MLST) of tobacco wildfire pathogen, and provide strong technical support for formulating effective control measures and breeding varieties, and a new perspective for biological characteristics study of the pathogen. Wildfire disease samples were collected from five tobacco production areas in Hunan, Chongqing and other provinces (Municipalities). And then tissue isolation and identification were carried out. MLST typing was applied to screen housekeeping gene, and the genetic diversity of the tested strains was analyzed. The results showed that 144 strains of tobacco wildfire pathogen were isolated from five tobacco producing provinces (Municipalities). Three housekeeping gene, Pgi, Pfk, and Gap were screened, and a total of 92 ST genotypes were obtained. Using the Pgi gene as the standard, the tested strains could be divided into 5 subgroups, 4 single groups, with a large number of subgroup 1 and subgroup 2 strains. The subgroup 1 strains came from 5 tobacco producing provinces (Municipalities), and ST43 of this subgroup belonged to the main population in China. It indicated that the genetic polymorphism of tobacco wildfire pathogens in China was rich, and there was no correlation between tobacco varieties and pathogen groups.

为了提高无人投饵船在含障碍物河蟹养殖池塘自主巡航的作业效率和安全性，该研究提出基于改进A*算法与人工势场法相融合（fusion of improved A* and artificial potential field，FIA*-APF）的蟹塘投饵船动态路径规划算法。首先引入动态加权因子优化A*算法评价函数；其次加入转折惩罚函数并删除冗余点，接着利用B样条曲线对全局路径进行平滑处理；最后将改进A*算法得到的全局路径作为改进人工势场法中的引力路径，生成投饵船自主巡航高效路径。根据养殖池塘创建静态和动态2种仿真环境，分别对传统人工势场法（traditional artificial potential field，TAPF）、基于A*和人工势场法的融合算法（the A* and artificial potential field，TA*-APF）和FIA*-APF算法的性能进行20次测试。仿真试验结果表明：2种环境下，FIA*-APF算法的平均规划时间是TAPF算法的17.23%，是TA*-APF算法的51.96%，平均指令节点数量比TAPF算法减少50.64%，比TA*-APF算法减少65.03%，平均路径长度比TA*-APF算法减少2.82%。蟹塘试验结果表明：FIA*-APF算法的规划时间为TAPF算法的38.16%，为TA*-APF的62.42%，路径长度比TAPF算法减少29.13%，比TA*-APF减少10.15%；另外，TAPF和TA*-APF算法规划路径上大于60°的转角分别是FIA*-APF算法的3.28和2.62倍，大于100°的转角分别是FIA*-APF算法的3.73和1.67倍，该研究算法规划的路径更高效平滑。研究结果可为无人投饵船自主导航提供参考。

With the increase of global temperature, heat stress has emerged as one of the major factors affecting plant growth and development. The substantial losses caused by heat, particularly for staple crops like rice, pose a significant impact on economic benefits. In order to unravel the molecular mechanisms underlying plant response to heat stress, the adverse effects of heat stress on the morphology, physiology, biochemistry and photosynthesis have been presented. Furthermore, the three molecular mechanisms employed by plants to cope with heat stress, including signal transduction pathways, transcriptional factor regulatory networks and the expression of heat-resistance related genes have been introduced as well. Based on these insights, this review suggests that bioinformatics, genetic engineering, cell biology and molecular biology may be further employed as tools for understanding the molecular mechanisms of heat stress in plants. At last, this review offers a prospective outlook on future research directions in this field.

为解决传统肥料养分利用率低，以及一般聚合物包膜肥料的膜材料难以降解、养分释放速率不可控等问题，该研究以聚乙烯醇（PVA）为膜基材，通过与壳聚糖（CS）共混、使用戊二醛（GA）交联、添加纳米SiO2 3种不同的方式，制备了3种膜：PVA/CS膜、PVA/CS/GA膜、PVA/CS/GA/纳米SiO2膜，此外，制备了纯PVA膜作为对比。对4种膜进行了吸水率（Q）、生物降解性（De）、养分渗透系数（Ps）等表征，结果表明：CS的添加提升了膜的生物降解率，GA交联可以延缓膜在土壤中的生物降解速率，而纳米SiO2的添加对膜的生物降解性影响不大，总体来说4种膜都显示出良好的生物降解性（77 d内的生物降解率在30%～60%）；相比于PVA膜，PVA/CS、PVA/CS/GA和PVA/CS/GA/纳米SiO2膜的吸水率分别降低43.00%、68.79%和82.73%；相比于PVA/CS膜，PVA/CS/GA和PVA/CS/GA/纳米SiO2膜的养分渗透系数分别降低48.51%和57.59%，说明CS的添加、GA的交联和纳米SiO2的添加都增强了PVA膜的疏水性。将4种膜液通过转鼓包衣机包覆在尿素颗粒表面制得了4种包膜尿素（PCU）颗粒（PCU-PVA、PCU-PVA/CS、PCU-PVA/CS/GA和PCU-PVA/CS/GA/纳米SiO2），分别使用土埋法测定和数学模型拟合了氮素释放行为，结果显示4种PCU的氮释放量达到90%时所需的时间分别为5、11、23、28 d；氮素释放行为符合一级动力学模型，释放速率常数（k）依次减小，分别为0.3 654、0.2 333、0.1 127、0.0 926，且与膜的养分渗透系数（Ps）呈线性关系$k = 377.51{P_{{s}}} $，相关系数（R2）为0.9 991。该研究提供了系列生物降解性能良好、养分释放速率可控的聚乙烯醇/壳聚糖膜材料，并成功地应用于包膜尿素颗粒的制备，更方便和有效地指导PCU的施用。