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Improving Quantitative and Qualitative Characteristics of Wheat (Triticum aestivum L.) through Nitrogen Application under Semiarid Conditions

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Phyton-International Journal of Experimental Botany 2023年第4期92卷 1001-1017页

作者： Muhammad Rafiq Muhammad Saqib Husnain Jawad Talha Javed Sadam Hussain Muhammad Arif Baber Ali Muhammad Sultan Ali Bazmi Ghulam Abbas Marjan Aziz Mohammad Khalid Al-Sadoon Aneela Gulnaz Sobhi F.Lamlom Muhammad Azeem Sabir Jameel Akhtar Agronomic Research Institute Ayub Agricultural Research InstituteFaisalabad38850Pakistan Depertment of Agronomy University of AgricultureFaisalabad38040Pakistan Department of Agronomy Northwest A&F UniversityYangling712100China Department of Plant Sciences Quaid-i-Azam UniversityIslamabad45320Pakistan Fodder Research Institute Sargodha Sargodha40100Pakistan Department of Agricultural Engineering Barani Agricultural Research InstituteChakwal48800Pakistan Department of Zoology College of ScienceKing Saud UniversityRiyadh11451Saudi Arabia Department of Biotechnology Yeungnam UniversityGyeongbuk38641Korea Plant Production Department Faculty of Agriculture Saba BashaAlexandria UniversityAlexandria21531Egypt Department of Forestry Range and Wildlife ManagementThe Islamia University of BahawalpurBahawalpur63100Pakistan

Nitrogen(N),the building block of plant proteins and enzymes,is an essential macronutrient for plant functions.A field experiment was conducted to investigate the impact of different N application rates(28,57,85,114,142,171,and 200 kg ha^(−1))on the performance of spring wheat(cv.Ujala-2016)during the 2017–2018 and 2018–2019 growing seasons.A control without N application was kept for comparison.Two years mean data showed optimum seed yield(5,461.3 kg ha^(−1))for N-application at 142 kg ha^(−1) whereas application of lower and higher rates of N did not result in significant and economically higher seed yield.A higher seed yield was obtained in the 2017–2018(5,595 kg ha^(−1))than in the 2018–2019(5,328 kg ha^(−1))growing seasons under an N application of 142 kg ha^(−1).It was attributed to the greater number of growing degree days in the first(1,942.35°C days)than in the second year(1,813.75°C).Higher rates of N(171 and 200 kg ha^(−1))than 142 kg ha^(−1) produced more number of tillers(i.e.,948,300 and 666,650 ha^(−1),respectively).However,this increase did not contribute in achieving higher yields.Application of 142,171,and 200 kg ha^(−1) resulted in 14.15%,15.0%and 15.35%grain protein concentrations in comparison to 13.15%with the application of 114 kg ha^(−1).It is concluded that the application of N at 142 kg ha^(−1) could be beneficial for attaining higher grain yields and protein concentrations of wheat cultivar Ujala-2016.

关键词： Economical yield growing degree days nitrogen Ujala-2016 wheat

Regional growth model for summer maize based on a logistic model:Case study in China

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International Journal of Agricultural and Biological Engineering 2022年第5期15卷 41-55页

作者： Yi Guo Yunhe Liu Quanjiu Wang Lijun Su Jihong Zhang Kai Wei State Key Laboratory of Eco-hydraulic in Northwest Arid Region of China Xi’an University of TechnologyXi’an 710048China School of Water Resource and Hydropower Xi’an University of TechnologyXi’an 710048China School of Science Xi’an University of TechnologyXi’an 710048China

The growing degree days(GDD)is an important factor for crop growth because it affects dry matter formation and crop yield.In this study,the universal logistic models were established employing GDD and the relative GDD(RGDD)as the main parameters to characterize summer maize growth indices such as plant height(H),leaf area index(LAI),and dry matter accumulation(DMA).The relationships were analyzed between the growth indices,harvest index(HI),water consumption,and yield in maize.By considering China as an example,the results showed that the logistic model performed well at simulating the changes in the summer maize growth indices in different regions and the universal model parameters were within specific ranges.Furthermore,the logistic model with RGDD as the independent variable was more suitable for modeling summer maize growth in large areas than GDD.The relationship between the maximum LAI and HI was described by a quadratic polynomial function.HI was optimal(0.53)when the maximum LAI was about 5.13.The maximum LAI,maximum H,and maximum DMA could be described by a quadratic polynomial function of water consumption during the growing season.The summer maize yield could be predicted with a binary quadratic equation using the maximum GDD and water consumption.This study confirmed that a logistic model can be used to establish a universal growth model for summer maize in large areas.Reasonable ranges of parameters were recommended for the logistic model,as well as the reasonable water consumption and each growth index value for summer maize.These results will be helpful for predicting the growth and yield of summer maize.

关键词： summer maize water consumption logistic model growing degree days growth index of crop

Alpine tundra species phenology is mostly driven by climate-related variables rather than by photoperiod

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Journal of Mountain Science 2020年第9期17卷 2081-2096页

作者： QUAGLIA Elena RAVETTO ENRI Simone PEROTTI Elisa PROBO Massimiliano LOMBARDI Giampiero LONATI Michele Department of Agricultural Forest and Food SciencesUniversity of TorinoLargo Paolo Braccini 210095Grugliasco(To)Italy Grazing Systems AgroscopeRoute de Duillier 501260NyonSwitzerland

The study of plant phenology has frequently been used to link phenological events to various factors,such as temperature or photoperiod.In the high-alpine environment,proper timing of the phenological cycle has always been crucial to overcome harsh conditions and potential extreme events(i.***.spring frosts)but little is known about the response dynamics of the vegetation,which could shape the alpine landscape in a future of changing climate.Alpine tundra vegetation is composed by an array of species belonging to different phytosociological optima and with various survival strategies,and snowbed communities are a relevant expression of such an extreme-climate adapted flora.We set eight permanent plots with each one in a snowbed located on the Cimalegna plateau in Northwestern Italy and then we selected 10 most recurring species among our plots,all typical of the alpine tundra environment and classified in 3different pools:snowbed specialists,grassland species and rocky debris species.For 3 years we registered the phenophases of each species during the whole growing season using an adaptation of the BBCH scale.We later focused on the three most biologically relevant phenophases,i.e.,flower buds visible,full flowering,and beginning of seed dispersion.Three important season-related variables were chosen to investigate their relationship with the phenological cycle of the studied species:(i)the Day Of Year(DOY),the progressive number of days starting from the 1 st of January,used as a proxy of photoperiod,(ii)days From Snow Melt(DFSM),selected to include the relevance of the snow dynamics,and(iii)growing degree days(GDD),computed as a thermal sum.Our analysis highlighted that phenological development correlated better with DFSM and GDD than with DOY.Indeed,models showed that DOY was always a worse predictor since it failed to overcome interannual variations,while DFSM and marginally GDD were better suited to predict the phenological development of most of the species,despite differences intemperature and snowmelt date

关键词： Alpine plants Climate change growing degree days Italian Alps Salix herbacea Snowbed vegetation

Deduction of a meteorological phenology indicator from reconstructed MODIS LST imagery

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Journal of Forestry Research 2020年第6期31卷 2205-2216页

作者： Chi Hong Lim Song Hie Jung Nam Shin Kim Chang Seok Lee Department of Bio and Environmnetal Technology Graduate SchoolSeoul Women’s UniversitySeoul Republic of Korea Research Team on Ecological and Natural Map National Institute of EcologySeocheon Choongnam Republic of Korea Department of Bio and Environmnetal Technology Seoul Women’s UniversitySeoul Republic of Korea

Phenology is a valuable attribute of vegetation to assess the biological impacts from climate change.A challenge of phenological research is to obtain information on both high temporal resolution and fine spatial scale observations.Here,we constructed an air temperature map based on temporal merging and spatial interpolation algorithms to overcome the cloud-related problem from the MODIS LST product.Then,we derived the accumulated growing degree days(AGDD)from the constructed mean air temperature map to use as a meteorological indicator.Further,we verified the indicator with the seasonal mean air temperature and the green-up date of a Quercus mongolica forest determined from the field-based measurements.The AGDD threshold for each Q.mongolica forest when the first leaf has unfolded was detected from the EXG trajectory extracted from digital camera images.A comparison between meteorological and MODIS-derived AGDD showed good agreement between them.There was also high consistency between DoYs extracted from AGDD and EVI based on curvature K for Q.mongolica forests of 30 sampling sites throughout South Korea.The results prove that microclimatic factors such as elevation,waterbody,and land-use intensity were faithfully reflected in the reconstructed images.Therefore,the results of this study could be applied effectively in areas where microclimatic variation is very severe and for monitoring phenology of undergrowth,which is difficult to detect from reflectance imaging.

关键词： Climate change Digital camera growing degree days MODIS Phenology Quercus mongolica

growing Season and Phenological Stages of Small Grain Crops in Response to Climate Change in Alaska

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American Journal of Climate Change 2021年第4期10卷 490-511页

作者： Mingyuan Cheng Mingchu Zhang Robert Mark Van Veldhuizen Charles Winsett Knight Agricultural and Forestry Experiment Station University of Alaska Fairbanks Fairbanks USA Division of Agriculture Alaska Department of Natural Resources Division of Agriculture Fairbanks USA

The climate change in Alaska has caused earlier spring snowmelt and the growing season expanded. However, the effect of climate change on crop phenological stages, heading (BBCH 55) and maturity (BBCH 85), is unknown. In this study, the trends of growing-season length (GSL), phenological stages of crops and climatic parameters, and the correlations between climatic parameters and the phenological stages were analyzed using the climate data and crop data over the period of 1978 to 2016. The longer GSL was found in Fairbanks (64.83˚N, 147.77˚W) and in Delta Junction (64.05˚N, 145.60˚W) but not in Palmer (61.60˚N, 149.11˚W). Sowing dates did not change significantly in three locations. The decreasing trends of heading and maturity of crops were observed but varied with location. Heading of barley and oat significantly advanced 3 and 3.1 d decade-1, respectively from 1989 to 2016 in Fairbanks while no change of heading was observed in Delta Junction and Palmer. Maturity of barley, oat and wheat significantly advanced 2.6, 3.8 and 3.9 d decade-1, respectively from 1978 to 2016 in Fairbanks (P < 0.05);maturity of oat and wheat significantly advanced 4.4 a

关键词： Heading Maturity Climate Change growing-Season Length growing degree days