1,327
Views
1
CrossRef citations to date
0
Altmetric
Articles

A comparison of field assessment methods for lucerne inoculation experiments

, , , & ORCID Icon
Pages 860-872 | Received 23 May 2022, Accepted 05 Aug 2022, Published online: 16 Aug 2022

References

  • Abadi HSK, Abadi ARV, Daneshian J, Abad HHS, Baghizadeh A. 2020. Evaluation of meliloti rhizobium activity effectiveness on quantitative properties of alfalfa by bacterial inoculation in the south-east of Iran. Nexo Rev Cient. 33:725–736. doi:10.5377/nexo.v33i02.10804.
  • af Geijersstam L, Frankow-Lindberg B. 2017. Fröblandningar med blålusern – närproducerat protein i ett torrare klimat (in Vallkonferens.). Uppsala: Sveriges lantbruksuniversitet.
  • Atumo TT, Jones CS. 2021. Varietal differences in yield and nutritional quality of alfalfa (Medicago sativa) accessions during 20 months after planting in Ethiopia. Trop Grassl-Forrajes Trop. 9:89–96. doi:10.17138/TGFT(9)89-96.
  • Bell LW, Lawrence J, Johnson B, Peoples MB. 2017. New ley legumes increase nitrogen fixation and availability and grain crop yields in subtropical cropping systems. Crop Pasture Sci. 68:11–26. doi:10.1071/CP16248.
  • Ben-Laouane R, Ait-El-Mokhtar M, Anli M, Boutasknit A, Ait Rahou Y, Raklami A, Oufdou K, Wahbi S, Meddich A. 2021. Green compost combined with mycorrhizae and rhizobia: a strategy for improving alfalfa growth and yield under field conditions. Gesunde Pflanzen. 73:193–207. doi:10.1007/s10343-020-00537-z.
  • Berenji S, Moot DJ, Moir JL, Ridgway H, Rafat A. 2017. Dry matter yield, root traits, and nodule occupancy of lucerne and Caucasian clover when grown in acidic soil with high aluminium concentrations. Plant Soil. 416:227–241. doi:10.1007/s11104-017-3203-3.
  • Berg WK, Lissbrant S, Cunningham SM, Brouder SM, Volenec JJ. 2018. Phosphorus and potassium effects on taproot C and N reserve pools and long-term persistence of alfalfa (Medicago sativa L.). Plant Sci. 272:301–308. doi:10.1016/j.plantsci.2018.02.026.
  • Boivin S, Lepetit M. 2020. Partner preference in the legume-rhizobia symbiosis and impact on legume inoculation strategies. Regul Nitrogen-Fixing Symbioses Legumes. 94:323–348. doi:10.1016/bs.abr.2019.09.016.
  • Bonilla I, Bolanos L. 2009. Mineral nutrition for legume-rhizobia symbiosis: B, Ca, N, P, S, K, Fe, Mo, Co, and Ni: a review. Org Farming, Pest Control Remediat Soil Pollut. 1:253–274. doi:10.1007/978-1-4020-9654-9_13.
  • Cartelat A, Cerovic ZG, Goulas Y, Meyer S, Lelarge C, Prioul JL, Barbottin A, Jeuffroy MH, Gate P, Agati G, Moya I. 2005. Optically assessed contents of leaf polyphenolics and chlorophyll as indicators of nitrogen deficiency in wheat (Triticum aestivum L). Field Crops Res. 91:35–49. doi:10.1016/j.fcr.2004.05.002.
  • Cerovic ZG, Masdoumier G, Ben Ghozlen N, Latouche G. 2012. A new optical leaf-clip meter for simultaneous non-destructive assessment of leaf chlorophyll and epidermal flavonoids. Physiol Plant. 146:251–260. doi:10.1111/j.1399-3054.2012.01639.x.
  • Daur I, Saad MM, Eida AA, Ahmad S, Shah ZH, Ihsan MZ, Muhammad Y, Sohrab SS, Hirt H. 2018. Boosting alfalfa (Medicago sativa L.) production with rhizobacteria from various plants in Saudi Arabia. Front Microbiol. 9:477. doi:10.3389/fmicb.2018.00477.
  • Defez R, Andreozzi A, Romano S, Pocsfalvi G, Fiume I, Esposito R, Angelini C, Bianco C. 2019. Bacterial IAA-delivery into Medicago root nodules triggers a balanced stimulation of C and N metabolism leading to a biomass increase. Microorganisms. 7:403. doi:10.3390/microorganisms7100403.
  • Eng LS, Ismail R, Hashim W, Baharum A. 2019. The use of VARI, GLI, and ViGreen formulas in detecting vegetation in aerial images. Int J Technol. 10:1385–1394. doi:10.14716/ijtech.v10i7.3275.
  • Gastal F, Lemaire G. 1997. N uptake and distribution in plant canopies. Diagn Nitrogen Dtatus Crops. 3–43. doi:10.1007/978-3-642-60684-7_1.
  • Jauregui JM, Mills A, Black DBS, Wigley K, Ridgway HJ, Moot DJ. 2019. Yield components of lucerne were affected by sowing dates and inoculation treatments. Eur J Agron. 103:1–12. doi:10.1016/j.eja.2018.10.005.
  • Lebourgeois V, Begue A, Labbe S, Houles M, Martine JF. 2012. A light-weight multi-spectral aerial imaging system for nitrogen crop monitoring. Precis Agric. 13:525–541. doi:10.1007/s11119-012-9262-9.
  • Li Q, Zhou D, Denton MD, Cong S. 2019. Alfalfa monocultures promote soil organic carbon accumulation to a greater extent than perennial grass monocultures or grass-alfalfa mixtures. Ecol Eng. 131:53–62. doi:10.1016/j.ecoleng.2019.03.002.
  • Liu Y, Wang J, Xiao Y, Shi X, Zeng Y. 2021. Diversity analysis of chlorophyll, flavonoid, anthocyanin, and nitrogen balance index of tea based on Dualex. Phyt-Int J Exp Bot. 90:1549–1558. doi:10.32604/phyton.2021.015557.
  • Maselli F, Chiesi M, Angeli L, Fibbi L, Rapi B, Romani M, Sabatini F, Battista P. 2020. An improved NDVI-based method to predict actual evapotranspiration of irrigated grasses and crops. Agric Water Manag. 233:106077. doi:10.1016/j.agwat.2020.106077.
  • Mills AM, Smith MC, Moot DJ. 2016. Relationships between dry matter yield and height of rotationally grazed dryland lucerne. J N Z Grassl. 78:185–196. doi:10.33584/jnzg.2016.78.504.
  • Misar CG, Xu L, Gates RN, Boe A, Johnson PS. 2015. Stand persistence and forage yield of 11 alfalfa (Medicago sativa) populations in semiarid rangeland. Rangel Ecol Manag. 68:79–85. doi:10.1016/j.rama.2014.12.012.
  • Mokarram M, Boloorani AD, Hojati M. 2016. Relationship between land cover and vegetation indices. case study: Eghlid plain, Fars province. Iran. Eur J Geogr. 7:48–60.
  • Mokarram M, Hojjati M, Roshan G, Negahban S. 2015. Modeling the behavior of vegetation indices in the salt dome of Korsia in north-east of Darab, Fars, Iran. Model Earth Syst Environ. 1:27. doi:10.1007/s40808-015-0029-y.
  • Motohka T, Nasahara KN, Oguma H, Tsuchida S. 2010. Applicability of green-red vegetation index for remote sensing of vegetation phenology. Remote Sens (Basel). 2:2369–2387. doi:10.3390/rs2102369.
  • Mouradi M, Bouizgaren A, Farissi M, Latrach L, Qaddoury A, Ghoulam C. 2016. Seed osmopriming improves plant growth, nodulation, chlorophyll fluorescence and nutrient uptake in alfalfa (Medicago sativa L.)—rhizobia symbiosis under drought stress. Sci Hortic. 213:232–242. doi:10.1016/j.scienta.2016.11.002.
  • Peoples MB, Brockwell J, Hunt JR, Swan AD, Watson L, Hayes RC, Li GD, Hackney B, Nuttall JG, Davies SL, Fillery IRP. 2012. Factors affecting the potential contributions of N-2 fixation by legumes in Australian pasture systems. Crop Pasture Sci. 63:759–786. doi:10.1071/CP12123.
  • Phyu P, Islam MR, Cruz PCS, Collard BCY, Kato Y. 2020. Use of NDVI for indirect selection of high yield in tropical rice breeding. Euphytica. 216:74. doi:10.1007/s10681-020-02598-7.
  • Picasso VD, Casler MD, Undersander D. 2019. Resilience, stability, and productivity of alfalfa cultivars in rainfed regions of North America. Crop Sci. 59:800–810. doi:10.2135/cropsci2018.06.0372.
  • Rice W, Penney D, Nyborg M. 1977. Effects of soil acidity on rhizobia numbers, nodulation and nitrogen-fixation by alfalfa and red-clover. Can J Soil Sci. 57:197–203. doi:10.4141/cjss77-024.
  • Rouse JW, Haas RH, Schell JA, Deering DW. 1974. Monitoring vegetation systems in the great plains with ERTS. NASA Spec Publ. 351:309.
  • Sangra A, Shahin L, Dhir SK. 2019. Long-term maintainable somatic embryogenesis system in alfalfa (Medicago sativa) using leaf explants: embryogenic sustainability approach. Plants-Basel. 8:278. doi:10.3390/plants8080278.
  • Schneider P, Roberts DA, Kyriakidis PC. 2008. A VARI-based relative greenness from MODIS data for computing the fire potential index. Remote Sens Environ. 112:1151–1167. doi:10.1016/j.rse.2007.07.010.
  • Simili FF, Silva Barbosa KR, Augusto JG, Menegatto LS, Mendonca GG, Bonacim PM, de Andrade Gimenes FM, Savegnago RP. 2019. Study of the chemical composition of Urochloa brizantha using the SPAD index, neural networks, multiple linear models, principal components and cluster analysis. Anim Feed Sci Technol. 258:114307. doi:10.1016/j.anifeedsci.2019.114307.
  • Sousa DO, Hansen HH, Hallin O, Nussio LG, Nadeau E. 2020. A two-year comparison on nutritive value and yield of eight lucerne cultivars and one red clover cultivar. Grass Forage Sci. 75:76–85. doi:10.1111/gfs.12459.
  • Tremblay N, Wang Z, Cerovic ZG. 2012. Sensing crop nitrogen status with fluorescence indicators. A Review. Agron Sustain Dev. 32:451–464. doi:10.1007/s13593-011-0041-1.
  • Trubins R. 2013. Land-use change in southern Sweden: before and after decoupling. Land Use Policy. 33:161–169. doi:10.1016/j.landusepol.2012.12.018.
  • Vannoppen A, Gobin A. 2021. Estimating farm wheat yields from NDVI and meteorological data. Agron-Basel. 11:946. doi:10.3390/agronomy11050946.
  • Vina A, Gitelson AA, Rundquist DC, Keydan G, Leavitt B, Schepers J. 2004. Remote sensing—monitoring maize (Zea mays L.) phenology with remote sensing. Agron J. 96(4):1139–1147. doi:10.2134/agronj2004.1139.
  • Wang W, Yao X, Yao XF, Tian YC, Liu XJ, Ni J, Cao WD, Zhu Y. 2012. Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat. Field Crops Res. 129:90–98. doi:10.1016/j.fcr.2012.01.014.
  • Wang Y, Wang DJ, Shi PH, Omasa KJ. 2014. Estimating rice chlorophyll content and leaf nitrogen concentration with a digital still color camera under natural light. Plant Methods. 10:36. doi:10.1186/1746-4811-10-36.
  • Wigley K, Ridgway HJ, Humphries AW, Ballard RA, Moot DJ. 2018. Increased lucerne nodulation in acid soils with Sinorhizobium meliloti and lucerne tolerant to low pH and high aluminium. Crop Pasture Sci. 69(10):1031–1040. doi:10.1071/CP18124.
  • Xu K, Wang H, Li X, Liu H, Chi D, Yu F. 2016. Identifying areas suitable for cultivation of Medicago sativa L. in a typical steppe of inner Mongolia. Environ Earth Sci. 75(4):341. doi:10.1007/s12665-016-5251-z.
  • Yu H, Wu H-S, Wang Z-J. 2010. Evaluation of SPAD and Dualex for in-season corn nitrogen status estimation. Acta Agron Sin. 36:840–847. doi:10.1016/S1875-2780(09)60051-1.
  • Zhou Z, Morel J, Parsons D, Kucheryavskiy SV, Gustaysson A-M. 2019. Estimation of yield and quality of legume and grass mixtures using partial least squares and support vector machine analysis of spectral data. Comput Electron Agric. 162:246–253. doi:10.1016/j.compag.2019.03.038.