Effects of music stimulus on behavior response,cortisol level,and horizontal immunity of growing pigs

An enriched environment is widely used to improve domestic animals’ welfare and promote their natural behaviors. Music can reduce abnormal behavior in humans, nonhuman primates, and rodents. However, little is known about the effects of music on pigs. This study aims to explore the effects of repeated music stimulation on the behavior, physiology, and immunity of growing pigs. A total of 72 hybrid piglets (Large White × Duroc × Minpig) were randomly divided into three groups, including music (Mozart K.448, 60 to 70 dB), noise (recorded mechanical noise, 80 to 85 dB), and control (natural background sound, <40 dB), and 6 h sound stimulation was given per day (1000 to 1600 hours) from 40 to 100 d of age. The behavioral activities of the pigs were observed during the music stimulation, and their serum cortisol, salivary cortisol, and serum immune indices were also measured. Compared with the control group, the music group and noise group increased activity but decreased lying of pigs (P < 0.05). A significant increase in tail-wagging, playing, and exploring behaviors of pigs was found in the music group (P < 0.05), and the noise significantly increased the aggressive behavior of the pigs (P < 0.05). Tail-wagging, playing, exploring, manipulating, and aggressive behaviors decreased over time. Short-term (8 d) music stimulus had a lower cortisol level than that of the noise and control groups (P < 0.05), whereas long-term (60 d) music stimulus increased immunoglobulin G (IgG), interleukin-2 (IL-2), and interferon-gamma (IFN-γ) levels (P < 0.05) and decreased interleukin-4 (IL-4) level (P < 0.05). Long-term noise stimulus significantly reduced the level of IgG (P < 0.05) but did not affect the level of IL-2, IL-4, and IFN-γ levels (P > 0.05). In conclusion, short-term music stimulus (8 d) reduced the stress response, whereas long-term music stimulus (60 d) enhanced the immune responses. In addition, the noise increased the aggressive behavior, and long-term noise reduced the immunity of the growing pigs.     

特早熟抗病棉花品种辽棉35选育及栽培技术

本文主要介绍辽棉35的选育过程、生物学特性、产量、纤维品质、抗病性及栽培技术要点。     

氮肥不同用量对北方粳稻群体质量及品质的影响

氮是植物体内氨基酸、蛋白质、核酸、辅酶以及光合色素分子等的组成成分,因此,氮的营养状况与许多生理过程密切相关。针对水稻氮肥用量过高这一突出问题,本试验研究了氮肥施用总量对北方粳稻产量及其构成因素、叶面积指数、干物质积累、群体库容量以及品质特征等方面的影响,进一步明确不同氮肥施用量条件下北方粳稻产量和品质形成的调控机制。结果表明,施氮量的增加对叶面积指数、光合势及群体生长率有促进作用,随着施氮量的增加,水稻最高茎数、最高分蘖数、分蘖穗数和分蘖穗比例有逐渐增加的趋势;增加施氮量会导致整精米率、蛋白质含量上升,精米白度、食味值、峰值粘度、最低粘度、崩解值、最终粘度值降低,但不同施氮量对直链淀粉含量影响不大。     

寨卡病毒SYBR GreenⅠreal-time PCR方法的建立及应用

为建立一种针对寨卡病毒的快速诊断方法,本研究根据寨卡病毒的3’端保守基因序列,设计合成1对引物,建立了检测寨卡病毒的荧光定量PCR方法。结果显示:所建立的检测方法的Ct值与标准品在1.41×10^1~1.41×10^10^ copies/μL具有良好的线性关系,相关性为1,斜率为-3.502;灵敏性结果显示,该方法的检测限度为1.41×10^1 copies/μL,是普通PCR的10000倍;特异性结果显示,对CHIKV、DENV和JEV无特异性扩增,特异性强;重复性试验结果显示,组内和组间变异系数均小于1%,重复性好。本研究建立的SYBR Green I real-time PCR检测方法,可用于寨卡病毒感染的快速诊断。     

耕作方式及秸秆还田对土壤性质、微生物碳源代谢及小麦产量的影响

以小麦品种济麦22为试验材料,采用裂区试验设计,耕作方式为主区,分别设常规翻耕(C)、深松(S)、旋耕(R)处理,副区为秸秆还田量,分别设秸秆全还田(P)和秸秆不还田(A)处理,采用Biolog Eco技术测定土壤微生物碳源代谢功能,并分析土壤基本理化性质和作物产量。结果显示:深松与秸秆还田均有利于土壤含水量和有机碳含量的提高,0～15 cm土层分别提高了9.78%和24.00%,15～30 cm土层分别提高了7.08%和15.81%;深松提高了15～30 cm土层的pH值6.67%,秸秆还田提高了0～15 cm土层的pH值4.32%。深松和秸秆还田均有利于代谢多样性(丰富度指数、香浓多样性指数)、碳源代谢强度的提高,0～15 cm土层分别提高了26.84%、3.84%和38.02%,15～30 cm土层分别提高了11.87%、 3.63%和14.74%。主成分分析表明常规翻耕秸秆不还田和旋耕耕作秸秆不还田碳源代谢功能相近,15～30 cm层次内常规翻耕秸秆全还田碳源代谢功能和深松耕作秸秆全还田处理相近。深松和秸秆还田平均提高了小麦产量5.82%,微生物碳源代谢功能与小麦产量具有极显著的相关性。     

4个甜樱桃品种在德州的引种表现及设施栽培技术

对引入山东德州的4个甜樱桃品种美早、萨米脱、布鲁克斯、拉宾斯进行了日光温室栽培试验,对其性状表现进行了观察。结果表明,4个品种均表现生长良好,适应性强,结果正常,果实品质优良,可以作为德州地区日光温室的栽培品种发展。简述了4个甜樱桃品种在日光温室的栽培技术。     

利用SOM聚类分析及主成分分析方法鉴定小麦品种萌发期耐盐性

为了研究不同小麦品种萌发期的耐盐性,为小麦萌发期耐盐性鉴定提供快速、准确的鉴定方法和理论依据。本研究以40个冬小麦品种为试验材料,通过主成分分析法(PCA)与神经网络自组织映射(SOM)聚类分析法,研究盐胁迫对40个小麦品种萌发期各项形态指标的影响。主成分分析法结果表明,发芽势、发芽率、最长根长、第一片叶长及胚芽鞘长在PCA下载荷量最大;根据SOM聚类分析结果,‘德抗961’等4个小麦品种属于高度耐盐品种,‘济麦22’等14个小麦品种属于耐盐性品种,‘济麦20’等16个品种属于中等耐盐性品种,‘鲁麦21’等6个小麦品种属于盐敏感性品种。发芽势、发芽率、最长根长、第一片叶长、胚芽鞘长能够作为萌发期小麦耐盐性筛选的主要评价指标,并且结合主成分、SOM聚类分析方法进行小麦萌发期耐盐性鉴定更为科学、方便。     

Three SNPs within exons of INHA and ACVR2B genes are significantly associated with litter size in Dazu black goats

The aim of this study was to analyse the association between single-nucleotide polymorphisms within INHA and ACVR2B and litter size in Dazu black goats. In total, twenty-two SNPs were genotyped in 190 individuals by SNaPshot and resequencing. The results showed that three SNPs (SNP_1, SNP_12 and SNP_13 in this study) were detected to have significant additive genetic effect on the recorded goat litter size (p < .05). The SNP_1 (NC_030809.1), a non-synonymous substitution of G for T at chr2-g. 28314990 in the exon 2 of INHA gene (NM_001285606.1), resulted in homozygote 2 (HOM2) contributed 0.25 and heterozygote (HET) contributed 0.12 larger litter than homozygote 1 (HOM1). Meanwhile, SNP_12 (Chr22-g. 11721225 A > T) and SNP_13 (Chr22-g. 11721227 A > C) (NC_030829.1) simultaneously mutated at the first and third position of a triplet AAA (lysine, K) in the exon 4 of ACVR2B gene (XM_018066623.1) had estimated genetic effects of HOM1 (0.00) and HOM2 (0.03) larger than HET (−0.12). In conclusion, one SNPs (chr2-g. 28314990 T > G) within the exon 2 of INHA and two SNPs (Chr22-g. 11721225 A > T and Chr22-g. 11721227 A > C) i n the exon 4 of ACVR2B gene were highly recommended as candidate markers of litter size in Dazu black goats. A large-scale association study to assess the impact of these variants on litter size is still necessary.     

基于部首嵌入和注意力机制的病虫害命名实体识别

为了解决农业病虫害命名实体识别过程中存在的内在语义信息缺失、局部上下文特征易被忽略和捕获长距离依赖能力不足等问题，以农业病虫害文本为研究对象，提出一种基于部首嵌入和注意力机制的农业病虫害命名实体识别模型(Chinese agricultural diseases and pests named entity recognition with joint radical embedding and self attention, RS-ADP)。首先，该模型将部首嵌入集成到字符嵌入中作为输入，用以丰富语义信息。其中，针对部首嵌入设计了3种特征提取策略，即卷积神经网络(Convolutional neural network, CNN)、双向长短时记忆网络(Bidirectional long short term memory network, BiLSTM) 和CNN-BiLSTM；其次，采用多层不同窗口尺寸的CNNs层提取不同尺度的局部上下文信息；然后，在BiLSTM提取全局序列特征的基础上，采用自注意力机制进一步增强模型提取更长距离依赖的能力；最后，采用条件随机场(Conditional random field, CRF)联合识别实体边界和划分实体类别。在包含11个类别和24715条标注样本的农业病虫害自制语料上进行了实验。结果表明，本文模型RS-ADP在该数据集上精确率、召回率和F1值分别为94.16%、94.47%和94.32%；在具体实体类别上，RS-ADP在作物、病害、虫害等易识别实体上F1值高达95.81%、97.76%和97.23%。同时，RS-ADP在草害、病原等难以识别实体上F1值仍保持86%以上。实验结果表明，本文所提模型能够有效识别农业病虫害命名实体，其识别精度优于其他模型，且具有一定的泛化性。