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ARS Home » Southeast Area » Canal Point, Florida » Sugarcane Field Station » Research » Publications at this Location » Publications at this Location

Publications at this Location

ARS scientists publish results of their research projects in many formats. Listed below are the publications from research projects conducted at this location.

Clicking on a publication title will take you to more information on the publication. Clicking on the reprint icon Repository URL will take you to the publication reprint.

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2022 Publications
(listed by order of acceptance date)

Current View: Peer Reviewed Publications Only

Show All Publications || Peer Reviewed Journal Publications Only

Displaying 1 to 12 of 12 Records

Enhancing prediction accuracy by incorporating known locus (Bru1) as fixed effect for brown rust resistance in sugarcane
(Peer Reviewed Journal)
(26-Oct-22)
Registration of ‘CP 14-1377’ sugarcane for organic soils in Florida Reprint Icon
(Peer Reviewed Journal)
(22-Oct-22)
Registration of ‘CP 14-1377’ sugarcane for organic soils in Florida Reprint Icon
(Peer Reviewed Journal)
(21-Oct-22)
Registration of ‘CP 14-1490’ sugarcane Reprint Icon
(Peer Reviewed Journal)
(14-Sep-22)
Accuracy of genomic prediction of yield and sugar traits in Saccharum spp. hybrids Reprint Icon
(Peer Reviewed Journal)
(6-Sep-22)
Registration of ‘CP 13-4474’ sugarcane for sand soils Reprint Icon
(Peer Reviewed Journal)
(15-Aug-22)
Registration of ‘CP 14-1934’ sugarcane for Florida organic soils Reprint Icon
(Peer Reviewed Journal)
(15-Aug-22)
Registration of ‘CP 14-1934’ sugarcane for Florida organic soils Reprint Icon
(Peer Reviewed Journal)
(15-Aug-22)
Prediction of morpho-physiological traits in sugarcane using aerial imagery and machine learning Reprint Icon
(Peer Reviewed Journal)
(4-Aug-22)
Sugarcane growth, physiological and yield responses to application of Trinexapac-ethyl (ModdusTM) in grand growth phase Reprint Icon
(Peer Reviewed Journal)
(23-Jul-22)
Responses of sugarcane genotypes to salinity stress during growth and flowering
(Peer Reviewed Journal)
(14-Jun-22)
Sugarcane yield prediction and genotype selection using unmanned aerial vehicle-based hyperspectral imaging and machine learning Reprint Icon
(Peer Reviewed Journal)
(6-May-22)