Please wait a minute...
Journal of Integrative Agriculture  2021, Vol. 20 Issue (10): 2613-2626    DOI: 10.1016/S2095-3119(20)63306-8
Special Issue: 麦类耕作栽培合辑Triticeae Crops Physiology · Biochemistry · Cultivation · Tillage
Crop Science Advanced Online Publication | Current Issue | Archive | Adv Search |
Rapid determination of leaf water content for monitoring waterlogging in winter wheat based on hyperspectral parameters
YANG Fei-fei1, LIU Tao2, WANG Qi-yuan3, DU Ming-zhu1, YANG Tian-le2, LIU Da-zhong1, LI Shi-juan1, LIU Sheng-ping1 
1 Key Laboratory of Agri-information Service Technology, Ministry of Agriculture and Rural Affairs/Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China
2 Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Agricultural College, Yangzhou University, Yangzhou 225009, P.R.China
3 College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing 100083, P.R.China
Download:  PDF in ScienceDirect  
Export:  BibTeX | EndNote (RIS)      
摘要  于极端降雨量事件的频繁发生,涝渍胁迫已成为粮食生产的明显制约因素。叶片含水量是一个重要的指标,且高光谱遥感为测定它提供了一种无损、实时且可靠的方法。因此,本文基于盆栽试验,于拔节期对冬小麦进行不同涝渍胁迫梯度处理。涝渍胁迫后每7天采集一次叶片高光谱数据、叶片含水量(leaf water content, LWC)数据,直至小麦成熟。结合植被指数构建、相关分析、回归分析、BP神经网络(BP neural network, BPNN)等方法,我们发现:(1)涝渍胁迫对叶片含水量的影响具有滞后性。(2)所有涝渍胁迫均会导致叶片含水量的降低。重度渍水下叶片含水量的下降速度比轻度渍水快,但长期轻度渍水比短期重度渍水对叶片含水量的影响程度更深。(3)叶片含水量的光谱敏感波段位于可见光(VIS, 400-780 nm)和短波红外(SWIR, 1400-2500 nm)波段。(4)以648 nm处原始光谱值,500 nm处一阶微分值,红边位置,新植被指数RVI (437, 466), NDVI (437, 466) 和NDVI' (747, 1956) 作为自变量建立的BPNN模型最适合反演涝渍胁迫冬小麦叶片含水量(建模集:R2=0.889, RMSE=0.138;验模集:R2=0.891, RMSE=0.518)。研究结果对涝渍胁迫精确防控具有重要的理论意义和实际应用价值。

Abstract  
Waterlogging is becoming an obvious constraint on food production due to the frequent occurrence of extremely high-level rainfall events.  Leaf water content (LWC) is an important waterlogging indicator, and hyperspectral remote sensing provides a non-destructive, real-time and reliable method to determine LWC.  Thus, based on a pot experiment, winter wheat was subjected to different gradients of waterlogging stress at the jointing stage.  Leaf hyperspectral data and LWC were collected every 7 days after waterlogging treatment until the winter wheat was mature.  Combined with methods such as vegetation index construction, correlation analysis, regression analysis, BP neural network (BPNN), etc., we found that the effect of waterlogging stress on LWC had the characteristics of hysteresis and all waterlogging stress led to the decrease of LWC.  LWC decreased faster under severe stress than under slight stress, but the effect of long-term slight stress was greater than that of short-term severe stress.  The sensitive spectral bands of LWC were located in the visible (VIS, 400–780 nm) and short-wave infrared (SWIR, 1 400–2 500 nm) regions.  The BPNN Model with the original spectrum at 648 nm, the first derivative spectrum at 500 nm, the red edge position (λr), the new vegetation index RVI (437, 466), NDVI (437, 466) and NDVI´ (747, 1 956) as independent variables was the best model for inverting the LWC of waterlogging in winter wheat (modeling set: R2=0.889, RMSE=0.138; validation set: R2=0.891, RMSE=0.518).  These results have important theoretical significance and practical application value for the precise control of waterlogging stress. 
Keywords:  winter wheat        hyperspectral remote sensing        leaf water content        new vegetation index        BP neural network  
Received: 22 February 2020   Accepted:
Fund: This work was supported by the National Key Research and Development Program of China (2016YFD0200600, 2016YFD0200601), the Key Research and Development Program of Hebei Province, China (19227407D); the Central Public-interest Scientific Institution Basal Research Fund (JBYW-AII-2020-29, JBYW-AII-2020-30); and the Technology Innovation Project Fund of Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2020-AII).
Corresponding Authors:  Correspondence LI Shi-juan, Tel: +86-10-82109916, E-mail: lishijuan@caas.cn; LIU Sheng-ping, Tel: +86-10-82109348, E-mail: liushengping@caas.cn    
About author:  YANG Fei-fei, E-mail: 82101172482@caas.cn;

Cite this article: 

YANG Fei-fei, LIU Tao, WANG Qi-yuan, DU Ming-zhu, YANG Tian-le, LIU Da-zhong, LI Shi-juan, LIU Sheng-ping. 2021. Rapid determination of leaf water content for monitoring waterlogging in winter wheat based on hyperspectral parameters. Journal of Integrative Agriculture, 20(10): 2613-2626.

Araki H, Hamada A, Hossain M A, Takahashi T. 2012. Waterlogging at jointing and/or after anthesis in wheat induces early leaf senescence and impairs grain filling. Field Crops Research, 137, 27–36.
Arshad M, Ullah S, Khurshid K, Ali A, Arshad M, Ullah S, Khurshid K, Ali A. 2017. Estimation of leaf water contents from mid- and thermal-infra red spectra by coupling genetic algorithm and partial least squares regression. In: Remote Sensing for Agriculture, Ecosystems and Hydrology XIX. Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, USA.
Atzberger C, Darvishzadeh R, Immitzer M, Schlerf M, Skidmore A, Maire G L. 2015. Comparative analysis of different retrieval methods for mapping grassland leaf area index using airborne imaging spectroscopy. International Journal of Applied Earth Observation & Geoinformation, 43, S1544033316.
Azimi-Sadjadi M R, Ghaloum S, Zoughi R. 1993. Terrain classification in SAR images using principal components analysis and neural networks. IEEE Transactions on Geoscience & Remote Sensing, 31, 515.
Bastawesy M E, Ali R R, Harbi K A, Faid A. 2012. Impact of the geomorphology and soil management on the development of waterlogging in closed drainage basins of Egypt and Saudi Arabia. Environmental Earth Sciences, 68, 1271–1283.
Broskinsky A, Lausch A, Doktor D, Salbach C, Pause M. 2014. Analysis of spectral vegetation signal characteristics as a function of soil moisture conditions using hyperspectral remote sensing. Journal of the Indian Society of Remote Sensing, 42, 311–324.
Cao Z, Wang Q, Zheng C. 2015. Best hyperspectral indices for tracing leaf water status as determined from leaf dehydration experiments. Ecological Indicators, 54, 96–107.
Celedonio R P D S, Abeledo L G, Mantese A I, Miralles D J. 2017. Differential root and shoot biomass recovery in wheat and barley with transient waterlogging during preflowering. Plant & Soil, 417, 1–18.
Cheng T, Rivard B, Sánchez-Azofeifa A. 2011. Spectroscopic determination of leaf water content using continuous wavelet analysis. Remote Sensing of Environment, 115, 659–670.
Cho M A, Skidmore A K, Atzberger C. 2008. Towards red edge positions less sensitive to canopy biophysical parameters for leaf chlorophyll estimation using properties optique spectrales des feuilles (prospect) and scattering by arbitrarily inclined leaves (sailh) simulated data. International Journal of Remote Sensing, 29, 2241–2255.
Chowdary V M, Chandran R V, Neeti N, Bothale R V, Srivastava Y K, Ingle P, Ramakrishnan D, Dutta D, Jeyaram A, Sharma J R. 2008. Assessment of surface and sub-surface waterlogged areas in irrigation command areas of Bihar state using remote sensing and GIS. Agricultural Water Management, 95, 766.
Clevers J G P W, Kooistra L, Schaepman M E. 2010. Estimating canopy water content using hyperspectral remote sensing data. International Journal of Applied Earth Observation & Geoinformation, 12, 119–125.
Defries R S, Townshend J R G. 1994. NDVI-derived land cover classifications at a global scale. International Journal of Remote Sensing, 15, 3567–3586.
Dobrowski S Z, Pushnik J C, Zarco-Tejada P J, Ustin S L. 2005. Simple reflectance indices track heat and water stress-induced changes in steady-state chlorophyll fluorescence at the canopy scale. Remote Sensing of Environment, 97, 403–414.
Du K, Xu L, Wu H, Tu B, Zheng B. 2012. Ecophysiological and morphological adaption to soil flooding of two poplar clones differing in flood-tolerance. Flora, 207, 106.
Emengini E J, Blackburn A, Theobald J C. 2013. Discrimination of plant stress caused by oil pollution and waterlogging using hyperspectral and thermal remote sensing. Journal of Applied Remote Sensing, 7, 87–97.
Feng W, Zhang H Y, Zhang Y S, Qi S L, Heng Y R, Guo B B, Ma D Y, Guo T C. 2016. Remote detection of canopy leaf nitrogen concentration in winter wheat by using water resistance vegetation indices from in-situ hyperspectral data. Field Crops Research, 198, 238–246.
Gamon J A, Peñuelas J, Field C B. 1992. A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sensing of Environment, 41, 35–44.
Gao P, Duan T, Christensen M, Nan Z, Liu Q, Meng F, Huang J. 2018. The occurrence of rust disease, and biochemical and physiological responses on Apocynum venetum plants grown at four soil water contents, following inoculation with Melampsora apocyni. European Journal of Plant Pathology, 150, 549–563.
Ge Y, Bai G, Stoerger V, Schnable J C. 2016. Temporal dynamics of maize plant growth, water use, and leaf water content using automated high throughput RGB and hyperspectral imaging. Computers and Electronics in Agriculture, 127, 625–632.
Gu Y W, Li S, Gao W, Wei H. 2015. Hyperspectral estimation of the cadmium content in leaves of Brassica rapa chinesis based on the spectral parameters. Acta Ecologica Sinica, 35, 4445–4453. (in Chinese)
Guo B B, Zhu Y J, Feng W, He L, Wu Y P, Zhou Y, Ren X X, Ma Y. 2018. Remotely estimating aerial N uptake in winter wheat using red-edge area index from multi-angular hyperspectral data. Science of the Total Environment, 633, 1329–1344.
Hunt E R, Daughtry C S T, Li L. 2016. Feasibility of estimating leaf water content using spectral indices from WorldView-3’s near-infrared and shortwave infrared bands. International Journal of Remote Sensing, 37, 388–402.
Jiang J B, Steven M D, He R, Chen Y, Du P, Guo H. 2015. Identifying the spectral responses of several plant species under CO2 leakage and waterlogging stresses. International Journal of Greenhouse Gas Control, 37, 1–11.
Jiang J B, Steven M D, He R Y, Cai Q K. 2013. Comparison and analysis of hyperspectral remote sensing identifiable models for different vegetation under waterlogging stress. Spectroscopy and Spectral Analysis, 33, 3106–3110.
Jong S M D, Addink E A, Doelman J C. 2014. Detecting leaf-water content in Mediterranean trees using high-resolution spectrometry. International Journal of Applied Earth Observations & Geoinformation, 27, 128–136.
Jordan C F. 1969. Derivation of leaf-area index from quality of light on the forest floor. Ecology, 50, 663–666.
Junttila S, Vastaranta M, Liang X, Kaartinen H, Hyyppä J. 2016. Measuring leaf water content with dual-wavelength intensity data from terrestrial laser scanners. Remote Sens-Basel, 9, 8.
Khan A, Tan D K Y, Afrid M Z, Luo H, Fahad S. 2017. Nitrogen fertility and abiotic stresses management in cotton crop: a review. Environmental Science & Pollution Research, 24, 1–16.
Kira O, Linker R, Gitelson A. 2015. Non-destructive estimation of foliar chlorophyll and carotenoid contents: Focus on informative spectral bands. International Journal of Applied Earth Observations & Geoinformation, 38, 251–260.
Li C Y, Cai J, Jiang D, Dai T B, Cao W X. 2011. Effects of hardening by pre-anthesis waterlogging on grain yield and quality of post-anthesis waterlogged wheat (Triticum aestivum L. cv. Yangmai 9). Acta Ecologica Sinica, 31, 1904–1910. (in Chinese)
Li M, Chu R, Yu Q, Abu I, Shuren C, Shen S. 2018. Evaluating structural, chlorophyll-based and photochemical indices to detect summer maize responses to continuous water stress. Water, 10, 500.
Li Y, Li Y, Hu D, Wang J, Li H, Zhang X, Chen Y, Chen D H. 2017. Effects of waterlogging on BT protein content and nitrogen metabolism in square of BT cotton. Acta Agronomica Sinica, 43, 1658. (in Chinese)
Liu W, Huang J, Wei C, Wang X, Mansaray L R, Han J, Zhang D, Chen Y. 2018. Mapping water-logging damage on winter wheat at parcel level using high spatial resolution satellite data. ISPRS Journal of Photogrammetry and Remote Sensing, 142, 243–256.
Ma Y, Xiong Q X, Zhu J Q, Jiang S Y. 2018. Early warning indexes determination of the crop injuries caused by waterlogging based on DHSVM model. Journal of Supercomputing, 76, 2435–2448.
Mcdowell N G, Fisher R A, Xu C, Domec J C, Pockman W T. 2013. Evaluating theories of drought-induced vegetation mortality using a multimodel-experiment framework. New Phytologist, 200, 304–321.
Mcfeeters S K. 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17, 1425–1432.
Nguyen L T T, Osanai Y, Lai K, Anderson I C, Bange M P, Tissue D T, Singh B K. 2018. Responses of the soil microbial community to nitrogen fertilizer regimes and historical exposure to extreme weather events: Flooding or prolonged-drought. Soil Biology and Biochemistry, 118, 227–236.
Pandey A C, Singh S K, Nathawat M S. 2010. Waterlogging and flood hazards vulnerability and risk assessment in Indo Gangetic plain. Natural Hazards, 55, 273–289.
Penuelas J, Pinol J, Ogaya R, Filella I. 1997. Estimation of plant water concentration by the reflectance Water Index WI (R900/R970). International Journal of Remote Sensing, 18, 2869–2875.
Ramoelo A, Dzikiti S, Van Deventer H, Maherry A, Cho M A, Gush M. 2015. Potential to monitor plant stress using remote sensing tools. Journal of Arid Environments, 113, 134–144.
Ramoelo A, Skidmore A K, Cho M A, Schlerf M, Mathieu R, Heitk-Nig I M A. 2012. Regional estimation of savanna grass nitrogen using the red-edge band of the spaceborne Rapid Eye sensor. International Journal of Applied Earth Observations & Geoinformation, 19, 151–162.
Rodríguez-Pérez J R, Ordóñez C, González-Fernández A B, Sanz-Ablanedo E, Valenciano J B, Marcelo V. 2018. Leaf water content estimation by functional linear regression of field spectroscopy data. Biosystems Engineering, 165, 36–46.
Rouse J W, Haas R H, Schell J A, Deering D W. 1973. Monitoring vegetation systems in the great plains with ERTS. Nasa Special Publication, 351, 309.
Sampathkumar T, Pandian B J, Jeyakumar P, Manickasundaram P. 2014. Effect of deficit irrigation on yield, relative leaf water content, leaf proline accumulation and chlorophyll stability index of cotton–maize cropping sequence. Experimental Agriculture, 50, 407–425.
Seelig H D, Hoehn A, Stodieck L S, Klaus D M, Adams W W, Emery W J. 2009. Plant water parameters and the remote sensing R1300/R1450 leaf water index: controlled condition dynamics during the development of water deficit stress. Irrigation Science, 27, 357–365.
Sevanto S, Mcdowell N G, Dickman L T, Pangle R, Pockman W T. 2014. How do trees die? A test of the hydraulic failure and carbon starvation hypotheses. Plant Cell & Environment, 37, 153–161.
Shen X, Dong Z, Chen Y. 2015. Drought and UV-B radiation effect on photosynthesis and antioxidant parameters in soybean and maize. Acta Physiologiae Plantarum, 37, 25.
Suárez L, Zarco-Tejada P J, González-Dugo V, Berni J A J, Sagardoy R, Morales F, Fereres E. 2009. Detecting water stress effects on fruit quality in orchards with time-series PRI airborne imagery. Remote Sensing of Environment, 114, 286–298.
Ullah S, Skidmore A K, Ramoelo A, Groen T A, Naeem M, Ali A. 2014. Retrieval of leaf water content spanning the visible to thermal infrared spectra. Isprs Journal of Photogrammetry & Remote Sensing, 93, 56–64.
Wang J, Zhao C, Huang W. 2008. Basis and application of quantitative remote sensing in agriculture. Science Press, Beijing. (in Chinese)
Wang X, Zhao C, Guo N, Li Y, Jian S, Yu K. 2015. Determining the canopy water stress for spring wheat using canopy hyperspectral reflectance data in loess plateau semiarid regions. Spectroscopy Letters, 48, 492–498.
Wolf A F. 2012. Using worldview-2 Vis-NIR multispectral imagery to support land mapping and feature extraction using normalized difference index ratios. In: Annual Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery. USA.
Wu H, Zhang P, Xu M, Zhuang L. 2018. Spatial-temporal variations of the risk of winter wheat loss suffered from spring waterlogging disaster in the middle and lower Yangtze river reaches. Resources and Environment in the Yangtze Basin, 27, 1152–1158.
Wu J, Chen T, Pan L. 2015. Spectrum variance analysis of tree leaves under the condition of different leaf water content. Spectroscopy and Spectral Analysis, 35, 1961–1966.
Xiong Q, Wang X, Wang Y. 2016. Spectral characteristics analysis of wheat damaged by subsurface waterlogging. Spectroscopy and Spectral Analysis, 36, 2558–2561.
Yang F, Wang Y, Wang J, Deng W, Liao L, Li M. 2011. Different eco-physiological responses between male and female Populus deltoides clones to waterlogging stress. Forest Ecology & Management, 262, 1971.
Yi Q, Wang F, Bao A, Jiapaer G. 2014. Leaf and canopy water content estimation in cotton using hyperspectral indices and radiative transfer models. International Journal of Applied Earth Observations & Geoinformation, 33, 67–75.
Yu W D, Feng L P, Liu R H. 2013. Research progress and prospective of waterlogging on maize. Journal of Maize Sciences, 21, 143–147.
Zhang F, Zhou G. 2015. Estimation of canopy water content by means of hyperspectral indices based on drought stress gradient experiments of maize in the North Plain China. Remote Sensing, 7, 15203–15223.
Zhang L, Zhou Z, Zhang G, Meng Y, Chen B, Wang Y. 2012. Monitoring the leaf water content and specific leaf weight of cotton (Gossypium hirsutum L.) in saline soil using leaf spectral reflectance. European Journal of Agronomy, 41, 103–117.
Zhang W, Li X, Zhao L. 2018. A fast hyperspectral feature selection method based on band correlation analysis. IEEE Geoence and Remote Sensing Letters, 15, 1750–1754.
Zhang Z, Tang B H, Li Z L, Tang R, Zhong R. 2017. Estimation of leaf water content using new vegetation indices combined by near- and middle infrared spectral reflectances. In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS). pp. 4016–4019.
[1] ZHANG Chong, WANG Dan-dan, ZHAO Yong-jian, XIAO Yu-lin, CHEN Huan-xuan, LIU He-pu, FENG Li-yuan, YU Chang-hao, JU Xiao-tang. Significant reduction of ammonia emissions while increasing crop yields using the 4R nutrient stewardship in an intensive cropping system[J]. >Journal of Integrative Agriculture, 2023, 22(6): 1883-1895.
[2] ZHAO Xiao-dong, QIN Xiao-rui, LI Ting-liang, CAO Han-bing, XIE Ying-he. Effects of planting patterns plastic film mulching on soil temperature, moisture, functional bacteria and yield of winter wheat in the Loess Plateau of China[J]. >Journal of Integrative Agriculture, 2023, 22(5): 1560-1573.
[3] LIU Xue-jing, YIN Bao-zhong, HU Zhao-hui, BAO Xiao-yuan, WANG Yan-dong, ZHEN Wen-chao. Physiological response of flag leaf and yield formation of winter wheat under different spring restrictive irrigation regimes in the Haihe Plain, China[J]. >Journal of Integrative Agriculture, 2021, 20(9): 2343-2359.
[4] ZHAI Li-chao, Lü Li-hua, DONG Zhi-qiang, ZHANG Li-hua, ZHANG Jing-ting, JIA Xiu-ling, ZHANG Zheng-bin. The water-saving potential of using micro-sprinkling irrigation for winter wheat production on the North China Plain[J]. >Journal of Integrative Agriculture, 2021, 20(6): 1687-1700.
[5] YAO Feng-mei, LI Qin-ying, ZENG Rui-yun, SHI Si-qi. Effects of different agricultural treatments on narrowing winter wheat yield gap and nitrogen use efficiency in China[J]. >Journal of Integrative Agriculture, 2021, 20(2): 383-394.
[6] MA Ming-yang, LIU Yang, ZHANG Yao-wen, QIN Wei-long, WANG Zhi-min, ZHANG Ying-hua, LU Cong-ming, LU Qing-tao. In situ measurements of winter wheat diurnal changes in photosynthesis and environmental factors reveal new insight into photosynthesis improvement by super-high-yield cultivation[J]. >Journal of Integrative Agriculture, 2021, 20(2): 527-539.
[7] LI Jin-peng, ZHANG Zhen, YAO Chun-sheng, LIU Yang, WANG Zhi-min, FANG Bao-ting, ZHANG Ying-hua. Improving winter wheat grain yield and water-/nitrogen-use efficiency by optimizing the micro-sprinkling irrigation amount and nitrogen application rate[J]. >Journal of Integrative Agriculture, 2021, 20(2): 606-621.
[8] WU Fen, ZHAI Li-chao, XU Ping, ZHANG Zheng-bin, Elamin Hafiz BAILLO, Lemessa Negasa TOLOSA, Roy Njoroge KIMOTHO, JIA Xiu-ling, GUO Hai-qian. Effects of deep vertical rotary tillage on the grain yield and resource use efficiency of winter wheat in the Huang-Huai-Hai Plain of China[J]. >Journal of Integrative Agriculture, 2021, 20(2): 593-605.
[9] ZHANG Pan-pan, CHEN Yu-lu, WANG Chen-yang, MA Geng, LÜ Jun-jie, LIU Jing-bao, GUO Tian-cai. Distribution and accumulation of zinc and nitrogen in wheat grain pearling fractions in response to foliar zinc and soil nitrogen applications[J]. >Journal of Integrative Agriculture, 2021, 20(12): 3277-3288.
[10] WANG Rui, WANG Ying, HU Ya-xian, DANG Ting-hui, GUO Sheng-li. Divergent responses of tiller and grain yield to fertilization and fallow precipitation: Insights from a 28-year long-term experiment in a semiarid winter wheat system[J]. >Journal of Integrative Agriculture, 2021, 20(11): 3003-3011.
[11] ZHANG Li, CHU Qing-quan, JIANG Yu-lin, CHEN Fu, LEI Yong-deng. Impacts of climate change on drought risk of winter wheat in the North China Plain[J]. >Journal of Integrative Agriculture, 2021, 20(10): 2601-2612.
[12] CHEN Ying, LIU Feng-shan, TAO Fu-lu, GE Quan-sheng, JIANG Min, WANG Meng, ZHAO Feng-hua. Calibration and validation of SiBcrop Model for simulating LAI and surface heat fluxes of winter wheat in the North China Plain[J]. >Journal of Integrative Agriculture, 2020, 19(9): 2206-2215.
[13] CAI Dong-yu, YAN Hai-jun, LI Lian-hao. Effects of water application uniformity using a center pivot on winter wheat yield, water and nitrogen use efficiency in the North China Plain[J]. >Journal of Integrative Agriculture, 2020, 19(9): 2326-2339.
[14] LIU Xin, WANG Wen-xin, LIN Xiang, GU Shu-bo, WANG Dong. The effects of intraspecific competition and light transmission within the canopy on wheat yield in a wide-precision planting pattern[J]. >Journal of Integrative Agriculture, 2020, 19(6): 1577-1585.
[15] CHEN Jin, PANG Dang-wei, JIN Min, LUO Yong-li, LI Hao-yu, LI Yong, WANG Zhen-lin.
Improved soil characteristics in the deeper plough layer can increase grain yield of winter wheat
[J]. >Journal of Integrative Agriculture, 2020, 19(5): 1215-1226.
No Suggested Reading articles found!