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Spatio-temporal variations in trends of vegetation and drought changes in relation to climate variability from 1982 to 2019 based on remote sensing data from East Asia
Shahzad ALI, Abdul BASIT, Muhammad UMAIR, Tyan Alice MAKANDA, Fahim Ullah KHAN, Siqi SHI, NI Jian
2023, 22 (10): 3193-3208.   DOI: 10.1016/j.jia.2023.04.028
Abstract117)      PDF in ScienceDirect      

Studying the significant impacts on vegetation of drought due to global warming is crucial in order to understand its dynamics and interrelationships with temperature, rainfall, and normalized difference vegetation index (NDVI).  These factors are linked to excesses drought frequency and severity on the regional scale, and their effect on vegetation remains an important topic for climate change study.  East Asia is very sensitive and susceptible to climate change.  In this study, we examined the effect of drought on the seasonal variations of vegetation in relation to climate variability and determined which growing seasons are most vulnerable to drought risk; and then explored the spatio-temporal evolution of the trend in drought changes in East Asia from 1982 to 2019.  The data were studied using a series of several drought indexes, and the data were then classified using a heat map, box and whisker plot analysis, and principal component analysis.  The various drought indexes from January to August improved rapidly, except for vegetation health index (VHI) and temperature condition index (TCI).  While these indices were constant in September, they increased again in October, but in December, they showed a descending trend.  The seasonal and monthly analysis of the drought indexes and the heat map confirmed that the East Asian region suffered from extreme droughts in 1984, 1993, 2007, and 2012 among the study years.  The distribution of the trend in drought changes indicated that more severe drought occurred in the northwestern region than in the southeastern area of East Asia.  The drought tendency slope was used to describe the changes in drought events during 1982–2019 in the study region.  The correlations among monthly precipitation anomaly percentage (NAP), NDVI, TCI, vegetation condition index (VCI), temperature vegetation drought index (TVDI), and VHI indicated considerably positive correlations, while considerably negative correlations were found among the three pairs of NDVI and VHI, TVDI and VHI, and NDVI and TCI.  This ecological and climatic mechanism provides a good basis for the assessment of vegetation and drought-change variations within the East Asian region.  This study is a step forward in monitoring the seasonal variation of vegetation and variations in drought dynamics within the East Asian region, which will serve and contribute to the better management of vegetation, disaster risk, and drought in the East Asian region.


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Improvement in winter wheat productivity through regulating PSII photochemistry, photosynthesis and chlorophyll fluorescence under deficit irrigation conditions
Shahzad AlI, XU Yue-yue, MA Xiang-cheng, JIA Qian-min, JIA Zhi-kuan
2022, 21 (3): 654-665.   DOI: 10.1016/S2095-3119(20)63409-8
Abstract134)      PDF in ScienceDirect      

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the Editor and Authors. The article was submitted by the first author Shahzad ALI without permission from corresponding author, Dr. JIA Zhi-kuan. The editor and corresponding author requested to retract the article. Apologies are offered to the readers of the journal.

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Developing a process-based and remote sensing driven crop yield model for maize (PRYM–Maize) and its validation over the Northeast China Plain
ZHANG Sha, Bai Yun, Zhang Jia-hua, Shahzad ALI
2021, 20 (2): 408-423.   DOI: 10.1016/S2095-3119(20)63293-2
Abstract100)      PDF in ScienceDirect      
Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing (RS) approaches limited their applications over broad regions. In this study, a process-based and remote sensing driven crop yield model for maize (PRYM–Maize) was developed to estimate regional maize yield, and it was implemented using eight data-model coupling strategies (DMCSs) over the Northeast China Plain (NECP). Simulations under eight DMCSs were validated against the prefecture-level statistics (2010–2012) reported by National Bureau of Statistics of China, and inter-compared. The 3-year averaged result could give more robust estimate than the yearly simulation for maize yield over space. A 3-year averaged validation showed that prefecture-level estimates by PRYM–Maize under DMCS8, which coupled with the development stage (DVS)-based grain-filling algorithm and RS phenology information and leaf area index (LAI), had higher correlation (R, 0.61) and smaller root mean standard error (RMSE, 1.33 t ha–1) with the statistics than did PRYM–Maize under other DMCSs. The result also demonstrated that DVS-based grain-filling algorithm worked better for maize yield than did the harvest index (HI)-based method, and both RS phenology information and LAI worked for improving regional maize yield estimate. These results demonstrate that the developed PRYM–Maize under DMCS8 gives reasonable estimates for maize yield and provides scientific basis facilitating the understanding the spatial variations of maize yield over the NECP.
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Effects of uniconazole with or without micronutrient on the lignin biosynthesis, lodging resistance, and winter wheat production in semiarid regions
Irshad AHMAD, MENG Xiang-ping, Muhammad KAMRAN, Shahzad ALI, Shakeel AHMAD, LIU Tie-ning, CAI Tie, HAN Qing-fang
2020, 19 (1): 62-77.   DOI: 10.1016/S2095-3119(19)62632-8
Abstract191)      PDF in ScienceDirect      
Lodging stress results in grain yield and quality reduction in wheat.  Uniconazole, a potential plant growth regulator significantly enhances lignin biosynthesis and thus provides mechanical strength to plants in order to cope with lodging stress.  A field study was conducted during the 2015–2016 and 2016–2017 growing seasons, to investigate the effects of uniconazole sole application or with micronutrient on the lignin biosynthesis, lodging resistance, and production of winter wheat.  In the first experiment, uniconazole at concentrations of 0 (CK), 15 (US1), 30 (US2), and 45 (US3) mg L–1 was applied as sole seed soaking, while in the second experiment with manganese (Mn) at concentration of 0.06 g L–1 Mn, 0.06 g L–1 Mn+15 mg L–1 uniconazole (UMS1), 0.06 g L–1 Mn+30 mg L–1 uniconazole (UMS2), and 0.06 g L–1 Mn+45 mg L–1 uniconazole (UMS3), respectively.  Uniconazole sole application or with micronutrient significantly increased the lignin content by improving the lignin-related enzyme activities of phenylalanine ammonia-lyase, cinnamyl alcohol dehydrogenase, tyrosine ammonia-lyase, and peroxidase, ameliorating basal internode characteristics, and breaking strength.  The spike length, spike diameter, spikes/plant, weight/spike, yield/spike, and grain yield increased and then decreased with uniconazole application at a higher concentration, where their maximum values were recorded with UMS2 and US2 treatments.  The lignin accumulation was positively correlated with lignin-related enzyme activities and breaking strength while, negatively correlated with lodging rate.  Uniconazole significantly improved the lignin biosynthesis, lodging resistance, and grain yield of winter wheat and the treatments which showed the greatest effects were uniconazole seed soaking with micronutrient at a concentration of 30 mg L–1 and 0.06 g L–1, and uniconazole sole seed soaking at a concentration of 30 mg L–1.
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