Early interspecific dynamics,dry matter production and nitrogen use in Kernza (Thinopyrum intermedium) – alfalfa (Medicago sativa L.) mixed intercropping

ABSTRACT

The global interest in growing perennial grain crops such as intermediate wheatgrass (Thinopyrum intermedium) (Kernza) for production of food and feed is increasing. Intercropping Kernza with legumes may be a sustainable way of supplying nitrogen to soil and associated intercrop. We determined the competitive interactions between intercropped Kernza (K) and alfalfa (Medicago sativa L.) (A) under three inorganic nitrogen (N) rates N0, N1, N2 (0, 200, 400 kg ha^?1) and five species relative frequencies (SRF) (100%K:0%A, 75%K:25%A, 50%K:50%A, 25%K:75%A and 0% K:100%A) in mixed intercrops (MI) in a greenhouse pot experiment. After 11 weeks of growth. Kernza dry matter yield (DM) and N accumulated (NACC) were low, but alfalfa DM and NACC high at 0 kg N ha^?1. 200 and 400 kg N ha^?1 fertiliser application increased the competitive ability (CA) of Kernza and reduced the CA of alfalfa. SRF had large impacts on alfalfa DM, NACC and NFIX only at 0 kg N ha^?1 fertiliser, and insignificant impacts on Kernza at all N fertiliser levels, indicating that adjustment of SRF may not be an effective way to modulate the interspecific competition of Kernza. Further research on the other factors that influence the interspecific competition are warranted.     

多效唑对杂交中稻不同密肥群体产量和抗倒伏性的影响

为探究高产稻田中防止倒伏发生的早期诊断技术,2015-2016年,以大面积推广的杂交中稻高产新品种蓉18优1015为试验材料,设计3因素完全因子试验,研究不同密肥群体下喷施多效唑对稻谷产量和抗倒伏性的影响。结果表明,随着施氮量和移栽密度的增加,稻谷产量提高,植株抗倒力下降,以施氮量150 kg·hm^-2和移栽密度18.75 万穴·hm^-2的产量较高。不同密肥群体下施用多效唑对产量和植株抗倒伏性有显著影响,施用多效唑后植株抗倒力增强,但产量因穗粒数下降而减少。不同密肥处理下施用多效唑对产量影响各异。于水稻最高苗期施用多效唑使植株重心高度、弯曲力矩、倒伏指数显著降低,折断弯矩则明显提高,穗粒数平均减少5.24~7.87粒。多效唑对产量的影响表现为低施氮量下因穗粒数减少而减产;中施氮量下产量差异不显著;高施氮量下植株未倒伏、籽粒灌浆结实正常,因结实率和千粒重高而增产。综上所述,肥力水平和施氮量高的稻田于最高苗期施用多效唑有利于水稻产量提高和控制后期倒伏。本研究为指导大面积水稻高产稳产提供了科学依据。     

生物炭对向日葵秸秆热解特性及气体产物影响

为了研究生物炭对向日葵秸秆热解的影响,以向日葵秸秆为原料,基于TG-FTIR研究生物炭添加前后向日葵秸秆热解特性与气体产物的变化。结果表明,与向日葵秸秆相比,混合样品主热解区间由276~349℃变得更长,并且发生不同程度的偏移,热解活化能不同程度降低,由60.21降到38.07~50.35 kJ/mol,呋喃类、酸类、含羰基类化合物、芳香醛类、CO、CH4等产物吸光度值存在差异。随着添加500℃制备生物炭比例增加,混合样品热解的活化能减小,释放气体产物中芳香醛类释放量增量减少,CO与CH4释放量降低。添加不同制备温度的生物炭,混合样品热解产生呋喃类、酸类、含羰基类化合物释放量均有所降低;添加500和700℃制备的生物炭,混合样品热解气体产物中芳香醛类增加。添加900℃制备的生物炭,向日葵秸秆热解气体产物中CO产量增加。该研究为向日葵秸秆的有效利用提供理论基础和技术支撑。     

林木氮素吸收偏好性及其形成机制研究进展

森林土壤中可被林木吸收利用的氮（N）素主要以铵态氮（NH₄+-N）和硝态氮（NO₃--N）的形态存在。受全球气候变暖、氮沉降和人类活动等因素的影响，NH₄+和NO₃-的分布存在很大的时间波动性和空间异质性，且NH₄+-N和NO₃--N亏缺已成为限制林地生产力的主要因素。在森林土壤N亏缺和N异质分布的逆境中，在林木长期进化过程中形成了对不同形态N素的吸收偏好，且这种吸收偏好会随生长环境条件而发生改变。特别是对于NH₄+和NO₃-这2种主要形态的偏好选择性已被证明是决定林木生产力、竞争、共存和生态演替的重要因素之一。对不同树种在N异质分布环境下的N吸收偏好和形成机制的研究，是揭示林木N素营养遗传特性和提高林地N素利用效率的关键。文中从森林土壤中N的主要形态及其分布特征、林木对不同形态N素的吸收偏好和形成机制、林木N吸收偏好的影响因素3个方面进行总结阐述，并对未来研究方向进行展望，以期为我国人工林培育中不同树种的造林配置和合理N素施肥技术提供理论依据和参考。     

高油酸花生品种开农1760产量及其构成的可视化分析

分析高油酸小粒花生品种开农1760的产量及其与农艺性状的关系,为高产优质育种提供有效指导。本研究以开农1760参加的2014-2015年河南省小粒花生区试数据为基础,运用GGE (genotype+genotype-by-environment interaction)双标图评价其丰产性和稳产性,利用R语言进行可视化的相关分析和通径分析。结果显示,开农1760的丰产稳产性综合排名第一,出米率的变异系数最小,饱果率与产量呈极显著正相关,百果重、单株生产力、百仁重、主茎高、侧枝长和结果枝数与产量呈显著正相关,结果枝数的直接通径系数最大,是影响开农1760荚果产量的关键性状。综上所述,开农1760丰产性好、稳定性强,适合在河南省大面积推广利用;在选育小粒花生新品种时可侧重做好对结果枝数的选择。     

我国楠属种质资源分布现状及主要种特征差异

对福建、江西、浙江、湖南、湖北、贵州、重庆、四川、海南、云南及广西11省(自治区、直辖市)70个县(区、市)的楠属(Phoebe)树种种质资源进行详细调查,记录楠属种质资源分布、群落现状、木材利用及人工造林情况,对种质资源进行收集保存,并详细介绍主要树种的特征差异。调查发现,中国楠属树种资源主要分布在长江流域及以南地区,其中紫楠(P.sheareri)、闽楠(P.bournei)及白楠(P.neurantha)分布范围最广;综合比较生长速度和适应性,广西适宜推广种植的楠属树种有闽楠、桢楠(P.zhennan)及崖楠(P.yaiensis)。     

江汉平原植棉区春玉米与短季棉套作的种植表现

为探索适宜江汉平原植棉区监利县旱地作物高产高效种植模式,开展了春玉米与短季棉套种模式示范试验。结果表明:春玉米与短季棉套种模式达到了玉米和棉花双丰收的高产效果,经济收益为33000元/hm^2左右,明显高于玉米和棉花的单作收益,是旱地作物结构调整的较好模式。     

Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index

Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop yield.Biomass is also a key trait in increasing grain yield by crop breeding.The aims of this study were(i)to identify the best vegetation indices for estimating maize biomass,(ii)to investigate the relationship between biomass and leaf area index(LAI)at several growth stages,and(iii)to evaluate a biomass model using measured vegetation indices or simulated vegetation indices of Sentinel 2A and LAI using a deep neural network(DNN)algorithm.The results showed that biomass was associated with all vegetation indices.The three-band water index(TBWI)was the best vegetation index for estimating biomass and the corresponding R2,RMSE,and RRMSE were 0.76,2.84 t ha−1,and 38.22%respectively.LAI was highly correlated with biomass(R2=0.89,RMSE=2.27 t ha−1,and RRMSE=30.55%).Estimated biomass based on 15 hyperspectral vegetation indices was in a high agreement with measured biomass using the DNN algorithm(R2=0.83,RMSE=1.96 t ha−1,and RRMSE=26.43%).Biomass estimation accuracy was further increased when LAI was combined with the 15 vegetation indices(R2=0.91,RMSE=1.49 t ha−1,and RRMSE=20.05%).Relationships between the hyperspectral vegetation indices and biomass differed from relationships between simulated Sentinel 2A vegetation indices and biomass.Biomass estimation from the hyperspectral vegetation indices was more accurate than that from the simulated Sentinel 2A vegetation indices(R2=0.87,RMSE=1.84 t ha−1,and RRMSE=24.76%).The DNN algorithm was effective in improving the estimation accuracy of biomass.It provides a guideline for estimating biomass of maize using remote sensing technology and the DNN algorithm in this region.