Please wait a minute...
Journal of Arid Land  2023, Vol. 15 Issue (10): 1231-1244    DOI: 10.1007/s40333-023-0108-2
Research article     
Nitrogen application levels based on critical nitrogen absorption regulate processing tomatoes productivity, nitrogen uptake, nitrate distributions, and root growth in Xinjiang, China
JING Bo1,2, SHI Wenjuan2, DIAO Ming1,*()
1Key Laboratory of Special Fruits and Vegetables Cultivation Physiology and Germplasm Resources Utilization of Xinjiang Production and Construction Corps, Department of Horticulture, Agricultural College, Shihezi University, Shihezi 832003, China
2State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi'an 710048, China
Download: HTML     PDF(1004KB)
Export: BibTeX | EndNote (RIS)      

Abstract  

The unreasonable nitrogen (N) supply and low productivity are the main factors restricting the sustainable development of processing tomatoes. In addition, the mechanism by which the N application strategy affects root growth and nitrate distributions in processing tomatoes remains unclear. In this study, we applied four N application levels to a field (including 0 (N0), 200 (N200), 300 (N300), and 400 (N400) kg/hm2) based on the critical N absorption ratio at each growth stage (planting stage to flowering stage: 22%; fruit setting stage: 24%; red ripening stage: 45%; and maturity stage: 9%). The results indicated that N300 treatment significantly improved the aboveground dry matter (DM), yield, N uptake, and nitrogen use efficiency (NUE), while N400 treatment increased nitrate nitrogen (NO3--N) residue in the 20-60 cm soil layer. Temporal variations of total root dry weight (TRDW) and total root length (TRL) showed a single-peak curve. Overall, N300 treatment improved the secondary root parameter of TRDW, while N400 treatment improved the secondary root parameter of TRL. The grey correlation coefficients indicated that root dry weight density (RDWD) in the surface soil (0-20 cm) had the strongest relationship with yield, whereas root length density (RLD) in the middle soil (20-40 cm) had a strong relationship with yield. The path model indicated that N uptake is a crucial factor affecting aboveground DM, TRDW, and yield. The above results indicate that N application levels based on critical N absorption improve the production of processing tomatoes by regulating N uptake and root distribution. Furthermore, the results of this study provide a theoretical basis for precise N management.



Key wordscritical N absorption      nitrogen use efficiency (NUE)      beta model      total root dry weight (TRDW)      root growth      processing tomato     
Received: 27 February 2023      Published: 31 October 2023
Corresponding Authors: *DIAO Ming (E-mail: diaoming@shzu.edu.cn)
About author: First author contact:

The second and third authors contributed equally to this work.

Cite this article:

JING Bo, SHI Wenjuan, DIAO Ming. Nitrogen application levels based on critical nitrogen absorption regulate processing tomatoes productivity, nitrogen uptake, nitrate distributions, and root growth in Xinjiang, China. Journal of Arid Land, 2023, 15(10): 1231-1244.

URL:

http://jal.xjegi.com/10.1007/s40333-023-0108-2     OR     http://jal.xjegi.com/Y2023/V15/I10/1231

Fig. 1 Daily precipitation, maximum temperature (Tmax), and minimum temperature (Tmin) during the growing season of processing tomatoes in 2018 (a) and 2019 (b)
Year pH Total N (g/kg) Available P (g/kg) Available K (g/kg) Organic matter (g/kg)
2018 7.53 0.85 0.02 0.34 10.12
2019 7.50 0.76 0.02 0.26 12.35
Table 1 Initial chemical properties of topsoil (0-40 cm) in 2018 and 2019
Fig. 2 (a), overhead view of the planting pattern of processing tomatoes in the experimental field; (b), stereoscopic view of root samples taken using the layered-mining method
Fig. 3 Aboveground dry matter (DM; a), yield (b), nitrogen (N) uptake (c), and nitrogen use efficiency (NUE; d) under different N application levels in 2018 and 2019. N0, N200, N300, and N400 represent the N application levels of 0, 200, 300, and 400 kg/hm2, respectively. Different lowercase letters in the same year indicate significant differences among different N application levels at P<0.05 level. ** indicates significance at P<0.01 level. Bars are standard errors.
Fig. 4 Beta model of the variations in total root dry weight (TRDW; a and b) and total root length (TRL; c and d) under different N application levels in 2018 and 2019. The fitting curves are the beta equation fitting curves of the N application levels at 0, 200, 300, and 400 kg/hm2.
Year Root
parameter
N application level Secondary root parameter
wmax (g/m2 or m/m2)# te (d) tm (d) ca ((g/m2)•d-1 or (m/m2)•d-1)## cm ((g/m2)•d-1 or (m/m2)•d-1)##
2018 TRDW N0 134.34d 86.62a 53.80c 1.55d 2.59d
N200 216.16c 84.99b 52.25c 2.54c 4.21c
N300 403.28a 81.60c 60.47a 4.94a 10.19a
N400 267.95b 79.90c 56.45b 3.35b 6.40b
TRL N0 355.76c 69.16a 43.05b 5.14c 8.59c
N200 408.77b 68.93a 41.14b 5.91b 9.61b
N300 581.57a 71.61a 42.61b 8.12a 13.14a
N400 596.53a 72.02a 47.24a 8.28a 14.48a
2019 TRDW N0 112.07d 88.03a 47.97b 1.27d 1.97d
N200 177.91c 81.47b 48.42b 2.02bc 3.53c
N300 308.10a 79.61b 57.08a 3.87a 7.55a
N400 222.65b 80.83b 56.17a 2.75b 5.14ab
TRL N0 348.19d 71.68a 47.20a 5.36b 8.53b
N200 371.98c 71.23a 45.19a 5.22b 8.86b
N300 514.03b 73.25a 42.58b 7.02a 11.20a
N400 555.99a 74.85a 47.21a 7.43a 12.54a
Table 2 Secondary root parameters under different N application levels
Fig. 5 Soil nitrate nitrogen (NO3--N) content in the 0-80 cm soil layers under different N application levels in 2018 (a) and 2019 (b). Bars are standard errors.
Fig. 6 Changes in root dry weight density (RDWD; a and b) and root length density (RLD; c and d) in different soil layers under different N application levels in 2018 and 2019. Bars are standard errors.
Root parameter N application level Soil depth (cm)
2018 2019
0-20 20-40 40-60 0-20 20-40 40-60
RDWD
(g/m3)
N0 0.649* 0.536 0.494 0.614 0.548 0.599
N200 0.651* 0.501 0.515 0.729** 0.544 0.587
N300 0.685 0.645 0.595 0.759* 0.677 0.657
N400 0.635 0.534 0.478 0.693 0.549 0.523
RLD
(m/m3)
N0 0.559 0.859** 0.557 0.641 0.727* 0.554
N200 0.573 0.676 0.508 0.583 0.637 0.540
N300 0.553 0.559 0.581 0.499 0.576 0.481
N400 0.673 0.757* 0.610 0.671 0.726 0.663
Table 3 Grey correlation coefficients between root parameters in different soil layers with yield under different N application levels
Fig. 7 Path model among aboveground DM, TRDW, N uptake, soil NO3--N content, and yield. Blue lines represent positive relationships, while red lines represent negative relationships. The width of the arrows represents the strength of significant standardised path coefficients. * and ** indicate significant path coefficient at P<0.05 and P<0.01 levels, respectively.
[1]   Ata-Ul-Karim S T, Zhu Y, Yao X, et al. 2014. Determination of critical nitrogen dilution curve based on leaf area index in rice. Field Crops Research, 167: 76-85.
doi: 10.1016/j.fcr.2014.07.010
[2]   Banger K, Wagner-Riddle C, Grant B B, et al. 2020. Modifying fertilizer rate and application method reduces environmental nitrogen losses and increases corn yield in Ontario. Science of The Total Environment, 722: 137851, doi: 10.1016/j.scitotenv.2020.137851.
[3]   Cheng M H, Wang H D, Fan J L, et al. 2021. Effects of nitrogen supply on tomato yield, water use efficiency and fruit quality: A global meta-analysis. Scientia Horticulturae, 290: 110553, doi: 10.1016/j.scienta.2021.110553.
[4]   Clark R T, MacCurdy R B, Jung J K, et al. 2011. Three-dimensional root phenotyping with a novel imaging and software platform. Plant Physiology, 156(2): 455-465.
doi: 10.1104/pp.110.169102 pmid: 21454799
[5]   Day K J, John E A, Hutchings M J. 2003. The effects of spatially heterogeneous nutrient supply on yield, intensity of competition and root placement patterns in Briza media and Festuca ovina. Functional Ecology, 17(4): 454-463.
doi: 10.1046/j.1365-2435.2003.00758.x
[6]   Drew M C. 1975. Comparison of the effects of a localized supply of phosphate, nitrate, ammonium and potassium on the growth of the seminal root system, and the shoot, in barley. New Phytologist, 75(3): 479-490.
doi: 10.1111/nph.1975.75.issue-3
[7]   Elia A, Conversa G. 2012. Agronomic and physiological responses of a tomato crop to nitrogen input. European Journal of Agronomy, 40: 64-74.
doi: 10.1016/j.eja.2012.02.001
[8]   Farneselli M, Benincasa P, Tosti G, et al. 2015. High fertigation frequency improves nitrogen uptake and crop performance in processing tomato grown with high nitrogen and water supply. Agricultural Water Management, 154: 52-58.
doi: 10.1016/j.agwat.2015.03.002
[9]   Farneselli M, Tosti G, Onofri A, et al. 2018. Effects of N sources and management strategies on crop growth, yield and potential N leaching in processing tomato. European Journal of Agronomy, 98: 46-54.
doi: 10.1016/j.eja.2018.04.006
[10]   Fenta B A, Beebe S E, Kunert K J, et al. 2014. Field phenotyping of soybean roots for drought stress tolerance. Agronomy Journal, 4(3): 418-435.
[11]   Forde B, Lorenzo H. 2001. The nutritional control of root development. Plant and Soil, 232: 51-68.
doi: 10.1023/A:1010329902165
[12]   Greenwood D J, Lemaire G, Gosse G, et al. 1990. Decline in percentage N of C3 and C4 crops with increasing plant mass. Annals of Botany, 66(4): 425-436.
doi: 10.1093/oxfordjournals.aob.a088044
[13]   Gu X B, Cai H J, Zhang Z T, et al. 2019. Ridge-furrow full film mulching: An adaptive management strategy to reduce irrigation of dryland winter rapeseed (Brassica napus L.) in northwest China. Agricultural and Forest Meteorology, 266-267: 119-128.
doi: 10.1016/j.agrformet.2018.12.009
[14]   Hackett C. 1972. A method of applying nutrients locally to roots under controlled conditions, and some morphological effects of locally applied nitrate on the branching of wheat roots. Australian Journal of Biological Sciences, 25(6): 1169-1180.
doi: 10.1071/BI9721169
[15]   Hermans C, Hammond J P, White P J, et al. 2006. How do plants respond to nutrient shortage by biomass allocation? Trends in Plant Science, 11(12): 610-617.
doi: 10.1016/j.tplants.2006.10.007 pmid: 17092760
[16]   Isobe K, Oka H, Watanabe T, et al. 2018. High soil microbial activity in the winter season enhances nitrogen cycling in a cool-temperate deciduous forest. Soil Biology & Biochemistry, 124: 90-100.
doi: 10.1016/j.soilbio.2018.05.028
[17]   Jia Q M, Yang L Y, An H Y, et al. 2020. Nitrogen fertilization and planting models regulate maize productivity, nitrate and root distributions in semi-arid regions. Soil & Tillage Research, 200: 104636, doi: 10.1016/j.still.2020.104636.
[18]   Jing B, Niu N, Zhang W L, et al. 2020. 15N tracer-based analysis of fertiliser nitrogen accumulation, utilisation and distribution in processing tomato at different growth stages. Acta Agriculturae Scandinavica Section B-Soil and Plant Science, 70(8): 620-627.
[19]   Jing B, Niu N, Zhang W L, et al. 2021. Effects of different nitrogen application rates on root architecture of processing tomatoes. Journal of Drainage and Irrigation Machinery Engineering, 39(12): 1257-1263. (in Chinese).
[20]   Kang S Z, Hao X M, Du T S, et al. 2017. Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice. Agricultural Water Management, 179: 5-17.
doi: 10.1016/j.agwat.2016.05.007
[21]   Li J, Lin W F. 2021. Effects of nitrogen fertilizer rates on the growth and nutrient utilization of calla lily intercropped with rubber trees. Soil & Tillage Research, 211: 105031, doi: 10.1016/j.still.2021.105031.
[22]   Li X L, Zhang X T, Niu J, et al. 2016. Irrigation water productivity is more influenced by agronomic practice factors than by climatic factors in Hexi Corridor, Northwest China. Scientific Reports, 6: 37971, doi: 10.1038/srep37971.
pmid: 27905483
[23]   Liang J P, He Z J, Shi W J. 2020. Cotton/mung bean intercropping improves crop productivity, water use efficiency, nitrogen uptake, and economic benefits in the arid area of Northwest China. Agricultural Water Management, 240: 106227, doi: 10.1016/j.agwat.2020.106277.
[24]   Liang J P, Shi W J. 2021. Poly-γ-glutamic acid improves water-stable aggregates, nitrogen and phosphorus uptake efficiency, water-fertilizer productivity, and economic benefit in barren desertified soils of Northwest China. Agricultural Water Management, 245: 106551, doi: 10.1016/j.agwat.2020.106551.
[25]   Litton C M, Raich J W, Ryan M G. 2007. Carbon allocation in forest ecosystems. Global Change Biology, 13: 2089-2109.
doi: 10.1111/gcb.2007.13.issue-10
[26]   Liu W X, Ma G, Wang C Y, et al. 2018. Irrigation and nitrogen regimes promote the use of soil water and nitrate nitrogen from deep soil layers by regulating root growth in wheat. Frontiers in Plant Science, 9: 32, doi: 10.3389/fpls.2018.00032.
pmid: 29449850
[27]   Liu Z X, Gao F, Liu Y, et al. 2019. Timing and splitting of nitrogen fertilizer supply to increase crop yield and efficiency of nitrogen utilization in a wheat-peanut relay intercropping system in China. Crop Journal, 7(1): 101-112.
doi: 10.1016/j.cj.2018.08.006
[28]   Long G Q, Li L H, Wang D, et al. 2021. Nitrogen levels regulate intercropping-related mitigation of potential nitrate leaching. Agriculture Ecosystems & Environment, 319: 107540, doi: 10.1016/j.agee.2021.107540.
[29]   Lovelli S, Scopa A, Perniola M, et al. 2012. Abscisic acid root and leaf concentration in relation to biomass partitioning in salinized tomato plants. Journal of Plant Physiology, 169: 226-233.
doi: 10.1016/j.jplph.2011.09.009 pmid: 22070973
[30]   Lu J, Shao G C, Cui J T, et al. 2019. Yield, fruit quality and water use efficiency of tomato for processing under regulated deficit irrigation: A meta-analysis. Agricultural Water Management, 222: 301-312.
doi: 10.1016/j.agwat.2019.06.008
[31]   Ning S R, Chen C, Zhou B B, et al. 2019. Evaluation of normalized root length density distribution models. Field Crops Research, 242: 107604, doi: 10.1016/j.fcr.2019.107604.
[32]   Martins A O, Omena-Garcia R P, Oliveira F S, et al. 2019. Differential root and shoot responses in the metabolism of tomato plants exhibiting reduced levels of gibberellin. Environmental and Experimental Botany, 157: 331-343.
doi: 10.1016/j.envexpbot.2018.10.036
[33]   Matiwane S E, Aremu A O, Valentine A J, et al. 2019. Nutritional status of KwaZulu-Natal soils affects microbe symbiosis, nitrogen utilization and growth of Vigna radiata (L.) R. Walczak. South African Journal of Botany, 126: 115-120.
doi: 10.1016/j.sajb.2019.06.007
[34]   McCarthy M C, Enquist B J. 2007. Consistency between an allometric approach and optimal partitioning theory in global patterns of plant biomass allocation. Functional Ecology, 21(4): 713-720.
doi: 10.1111/fec.2007.21.issue-4
[35]   Postma J A, Dathe A, Lynch J P. 2014. The optimal lateral root branching density for maize depends on nitrogen and phosphorus availability. Plant Physiology, 166(2): 590-602.
doi: 10.1104/pp.113.233916 pmid: 24850860
[36]   Ronga D, Zaccardelli M, Lovelli S, et al. 2017. Biomass production and dry matter partitioning of processing tomato under organic vs conventional cropping systems in a Mediterranean environment. Scientia Horticulturae, 224: 163-170.
doi: 10.1016/j.scienta.2017.05.037
[37]   Sainju U M, Allen B L, Lenssen A W, et al. 2017. Root biomass, root/shoot ratio, and soil water content under perennial grasses with different nitrogen rates. Field Crops Research, 210: 183-191.
doi: 10.1016/j.fcr.2017.05.029
[38]   Shi Z G, Wei F, Wan R, et al. 2022. Comprehensive evaluation of nitrogen use efficiency of different Lycium barbarum L. cultivars under nitrogen stress. Scientia Horticulturae, 295: 110807, doi: 10.1016/j.scienta.2021.110807.
[39]   Sun Y B, Bi H X, Xu H S, et al. 2018. Variation of fine roots distribution in apple (Malus pumila M.) -crop intercropping systems on the loess plateau of China. Agronomy Journal, 8(12): 1-16.
doi: 10.2134/agronj1916.00021962000800010001x
[40]   Tei F, Benincasa P, Guiducci M. 2002. Critical nitrogen concentration in processing tomato. European Journal Agronomy, 18(1-2): 45-55.
doi: 10.1016/S1161-0301(02)00096-5
[41]   Ulrich A. 1952. Physiological bases for assessing the nutritional requirements of plants. Annual Review of Plant Physiology, 3(1): 207-228.
doi: 10.1146/arplant.1952.3.issue-1
[42]   Walch-liu P, Neumann G, Engels C. 2001. Response of shoot and root growth to supply of different nitrogen forms is not related to carbohydrate and nitrogen status of tobacco plants. Journal of Plant Nutrition Soil Science, 164(1): 97-103.
doi: 10.1002/(ISSN)1522-2624
[43]   Wang J W, Du Y D, Niu W Q, et al. 2022. Drip irrigation mode affects tomato yield by regulating root-soil-microbe interactions. Agricultural Water Management, 260: 107188, doi: 10.1016/j.agwat.2021.107188.
[44]   Wang X, Ma F Y, Diao M, et al. 2013. Simulation of critical nitrogen concentration, nitrogen absorption and nitrogen nutrition index of drip irrigation tomato. Transactions of the Chinese Society of Agricultural Engineering, 29(18): 99-108. (in Chinese).
[45]   Wang Y H, Hu W L, Zhang X L, et al. 2014. Effects of cultivation patterns on winter wheat root growth parameters and grain yield. Field Crops Research, 156: 208-218.
doi: 10.1016/j.fcr.2013.11.017
[46]   Wang Y, Zhu Y C, Zhang S X, et al. 2018. What could promote farmers to replace chemical fertilizers with organic fertilizers? Journal of Cleaner Production, 199: 882-890.
doi: 10.1016/j.jclepro.2018.07.222
[47]   Wang Z H, Li S X. 2019. Nitrate N loss by leaching and surface runoff in agricultural land: A global issue (a review). Advances in Agronomy, 156: 159-217.
[48]   Xiang P A, Zhou Y, Huang H, et al. 2007. Discussion on the green tax stimulation measure of nitrogen fertilizer non-point source pollution control-taking the Dongting Lake area in China as a case. Agricultural Sciences in China, 6(6): 732-741.
doi: 10.1016/S1671-2927(07)60106-0
[49]   Yan D Z, Long X E, Ye L L, et al. 2021. Effects of salinity on microbial utilization of straw carbon and microbial residues retention in newly reclaimed coastal soil. European Journal Soil Biology, 107: 103364, doi: 10.1016/j.ejsobi.2021.103364.
[50]   Yin X Y, Goudriaan J, Lantinga E A, et al. 2002. A flexible sigmoid function of determinate growth. Annals of Botany, 91(3): 361-371.
doi: 10.1093/aob/mcg029
[51]   Yuan S N, Tan Z X, Huang Q Y. 2018. Migration and transformation mechanism of nitrogen in the biomass-biochar-plant transport process. Renewable & Sustainable Energy Reviews, 85: 1-13.
[52]   Zaman I, Ali M, Shahzad K, et al. 2021. Effect of plant spacings on growth, physiology, yield and fiber quality attributes of cotton genotypes under nitrogen fertilization. Agronomy Journal, 11: 2589, doi: 10.3390/agronomy11122589.
[53]   Zhang H, Forde B G. 1998. An Arabidopsis MADS box gene that controls nutrient-induced changes in root architecture. Science, 279: 407-409.
doi: 10.1126/science.279.5349.407 pmid: 9430595
[54]   Zheng J, Fan J L, Zhang F C, et al. 2021. Interactive effects of mulching practice and nitrogen rate on grain yield, water productivity, fertilizer use efficiency and greenhouse gas emissions of rainfed summer maize in northwest China. Agricultural Water Management, 248: 106778, doi: 10.1016/j.agwat.2021.106778.
[55]   Zhu L X, Liu L T, Sun H C, et al. 2022. The responses of lateral roots and root hairs to nitrogen stress in cotton based on daily root measurements. Journal of Agronomy and Crop Science, 208(1): 89-105.
doi: 10.1111/jac.v208.1
[56]   Zotarelli L, Scholberg J M, Dukes M D, et al. 2009. Tomato yield, biomass accumulation, root distribution and irrigation water use efficiency on a sandy soil, as affected by nitrogen rate and irrigation scheduling. Agricultural Water Management, 96(1): 23-34.
doi: 10.1016/j.agwat.2008.06.007
[1] JIA Hao, WANG Zhenhua, ZHANG Jinzhu, LI Wenhao, REN Zuoli, JIA Zhecheng, WANG Qin. Effects of biodegradable mulch on soil water and heat conditions, yield and quality of processing tomatoes by drip irrigation[J]. Journal of Arid Land, 2020, 12(5): 819-836.
[2] Ke ZHANG, ChangYan TIAN, ChunJian LI. Root growth and spatio-temporal distribution of three common annual halophytes in a saline desert, northern Xinjiang[J]. Journal of Arid Land, 2012, 4(3): 330-341.