In temperate climates, cold stress constrains productivity
of white clover (
Trifolium repens
L.), the most important
perennial forage legume in intensive grazing systems for
ruminants. Metabolism of water sugar carbohydrate (WSC)
has been proposed as an important trait conferring cold
tolerance to white clover. Conventional methodologies for
WSC determination are considered high-cost and time-consuming.
Near-infrared (NIR) spectroscopy is a robust,
reliable, and high-throughput methodology to estimate
chemical composition of forage species. The objectives
of this work were to determine the accuracy of NIR
spectroscopy for predicting WSC in stolon samples of white
clover, and to evaluate the genetic relationship between
WSC and cold tolerance. A white clover association mapping
(WCAM) population was stablished in three location that
represent a winter low temperature gradient associated with
altitude. Dry matter production and some morphological
traits were evaluated during three growing seasons. Samples
for WSC determination were collected three time during a
winter period. Samples were scanned with a NIR system,
and a prediction model for WSC was fitted using partial least
squares (PLS) regression. The adjusted prediction model
achieved suitable predictive ability (R
2 > 0.85). The WSC
per se did not show significant genetic relationship with
morphological and agronomically important traits. However,
the WSC degradation rate (WSCdr) across the winter period
showed significant genetic correlation with DM production
during spring (r
g = 0.64), which is the result of genetic/
physiological mechanism expressed during the cold period.
The NIR spectroscopy is a reliable and high-throughput
methodology to predict WSC in stolon samples of white
clover. The metabolism of WSC, evaluated as WSCdr, is
involved in the cold tolerance of the WCAM population.
The methodology implemented in this work is suitable to be
applied in a plant breeding program routine.
