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      Effect of water and nitrogen coupling regulation on the growth, physiology, yield, and quality attributes and comprehensive evaluation of wolfberry ( Lycium barbarum L.)


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          The characteristics of the growing environment (arid and semi-arid regions with abundant light), wastage of water, types of fertilizers used, quality of the plants, and the decline in yield due to the need for large quantities of water and fertilizers are the most significant obstacles to wolfberry cultivation. To cope with the scarcity of water caused by the increase in the area of wolfberry cultivation and to improve the efficiency of the utilization of water and fertilizers, a two-year field experiment was conducted in a typical area of the central dry zone of Ningxia in 2021 and 2022. The effects of different water and nitrogen coupling on the physiology, growth, quality, and yield of wolfberry were investigated, and a water and nitrogen management model with better indicators was constructed based on the TOPSIS model and a comprehensive scoring method. In the experiment, three irrigation quotas of 2,160, 2,565, and 2,970 m 3 ha –1 (I 1, I 2, and I 3) and three N applications of 165, 225, and 285 kg ha –1 (N 1, N 2, and N 3) were established; the local conventional management served as the control (CK). The results showed that the growth index of wolfberry was most significantly affected by irrigation, followed by the water and nitrogen interaction effect, and the nitrogen application had the least effect. The growth and development of wolfberry plants mainly takes place during the fruit ripening and flowering periods, and growth almost stops after entering the fruit ripening period. The chlorophyll (SPAD) values were affected by irrigation and nitrogen application to a significant level, except for during the spring tip period, but the effect of water and nitrogen interaction was not significant. The SPAD values of N2 treatment were better under different irrigation. The daily photosynthetic activity of wolfberry leaves peaked between 10:00 am and noon. The daily photosynthetic dynamics of wolfberry were affected by irrigation and nitrogen application to a significant level during the fruit ripening period, and the transpiration rate and leaf water use efficiency were affected by water and nitrogen interaction to a significant level during 8:00 am and noon, while the effect was not significant during the spring tip period. The yield, dry-to-fresh ratio, and 100 grain weight of wolfberry were significantly affected by the irrigation, nitrogen application, and their interaction effects. Specifically, the two-year yield with I 2N 2 treatment increased by 7.48% and 3.73%, respectively, compared to CK. The quality indices were significantly affected by irrigation and nitrogen application, except for the total sugars; other indexes were also significantly affected by water and nitrogen interaction effects. The evaluation of the TOPSIS model showed that the I 3N 1 treatment yielded the best quality of wolfberry, and the results of the integrated scoring method based on the growth, physiology, yield, and quality indicators and water-saving objectives showed that the I 2N 2 (2,565 m3 ha -1, 225 kg ha -1) treatment was the optimal water and nitrogen management mode for drip-irrigated wolfberry. Our findings provide a scientific basis for the optimal irrigation and management of fertilization of wolfberry in arid regions.

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          Our meta-analysis of 126 nitrogen addition experiments evaluated nitrogen (N) limitation of net primary production (NPP) in terrestrial ecosystems. We tested the hypothesis that N limitation is widespread among biomes and influenced by geography and climate. We used the response ratio (R approximately equal ANPP(N)/ANPP(ctrl)) of aboveground plant growth in fertilized to control plots and found that most ecosystems are nitrogen limited with an average 29% growth response to nitrogen (i.e., R = 1.29). The response ratio was significant within temperate forests (R = 1.19), tropical forests (R = 1.60), temperate grasslands (R = 1.53), tropical grasslands (R = 1.26), wetlands (R = 1.16), and tundra (R = 1.35), but not deserts. Eight tropical forest studies had been conducted on very young volcanic soils in Hawaii, and this subgroup was strongly N limited (R = 2.13), which resulted in a negative correlation between forest R and latitude. The degree of N limitation in the remainder of the tropical forest studies (R = 1.20) was comparable to that of temperate forests, and when the young Hawaiian subgroup was excluded, forest R did not vary with latitude. Grassland response increased with latitude, but was independent of temperature and precipitation. These results suggest that the global N and C cycles interact strongly and that geography can mediate ecosystem response to N within certain biome types.
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            The evolution and future of Earth's nitrogen cycle.

            Atmospheric reactions and slow geological processes controlled Earth's earliest nitrogen cycle, and by ~2.7 billion years ago, a linked suite of microbial processes evolved to form the modern nitrogen cycle with robust natural feedbacks and controls. Over the past century, however, the development of new agricultural practices to satisfy a growing global demand for food has drastically disrupted the nitrogen cycle. This has led to extensive eutrophication of fresh waters and coastal zones as well as increased inventories of the potent greenhouse gas nitrous oxide (N(2)O). Microbial processes will ultimately restore balance to the nitrogen cycle, but the damage done by humans to the nitrogen economy of the planet will persist for decades, possibly centuries, if active intervention and careful management strategies are not initiated.
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                Author and article information

                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                21 June 2023
                : 14
                : 1130109
                [1] 1 School of Civil and Water Engineering, Ningxia University , Yingchuan, China
                [2] 2 Ministry of Education Engineering Research Center for Modern Agricultural Water Resources Efficient Utilization in Dry Areas, Ningxia University , Yingchuan, China
                [3] 3 Ningxia Water-saving Irrigation and Water Resources Control Engineering Technology Research Center, Ningxia University , Yingchuan, China
                Author notes

                Edited by: Rangjian Qiu, Wuhan University, China

                Reviewed by: Liu Zhandong, Chinese Academy of Agricultural Sciences, China; Josep Rufat, Institute of Agrifood Research and Technology (IRTA), Spain

                *Correspondence: Juan Yin, yj7115@ 123456126.com
                Copyright © 2023 Ma, Yin, Yang, Sun and Yang

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                : 22 December 2022
                : 27 March 2023
                Page count
                Figures: 9, Tables: 7, Equations: 10, References: 63, Pages: 19, Words: 9437
                This research was supported by the Natural Science Foundation Project of Ningxia (2022AAC03032), the Ningxia First-class Discipline Construction Funding Project for Higher Education Institutions (Grant No. NXYLXK2021A03), and the Graduate Student Innovation Projects of Ningxia University (CCXM2022-19).
                Plant Science
                Original Research
                Custom metadata
                Plant Abiotic Stress

                Plant science & Botany
                water-nitrogen coupling,photosynthetic daily dynamics,topsis model,composite scoring method,multi-objective optimization,wolfberry


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