The importance of genotyping within the climate-smart plant breeding value chain – integrative tools for genetic enhancement programs
Frontiers in Plant Science,
Journal Year:
2025,
Volume and Issue:
15
Published: Feb. 6, 2025
The
challenges
faced
by
today's
agronomists,
plant
breeders,
and
their
managers
encompass
adapting
sustainably
to
climate
variability
while
working
with
limited
budgets.
Besides,
are
dealing
a
multitude
of
issues
different
organizations
on
similar
initiatives
projects,
leading
lack
sustainable
impact
smallholder
farmers.
To
transform
the
current
food
systems
as
more
resilient
model
efficient
solutions
needed
deliver
convey
results.
Challenges
such
logistics,
labour,
infrastructure,
equity,
must
be
addressed
alongside
increasingly
unstable
conditions
which
affect
life
cycle
transboundary
pathogens
pests.
In
this
context,
transforming
go
far
beyond
just
farmers
breeders
it
requires
substantial
contributions
from
industry,
global
finances,
transportation,
energy,
education,
country
developmental
sectors
including
legislators.
As
result,
holistic
approach
is
essential
for
achieving
sustain
population
anticipated
reach
9.7
billion
2050
11.2
2100.
2021,
nearly
193
million
individuals
were
affected
insecurity,
40
than
in
2020.
Meanwhile,
digital
world
rapidly
advancing
economy
estimated
at
about
20%
gross
domestic
product,
suggesting
that
technologies
accessible
even
areas
insecurity.
Leveraging
these
can
facilitate
development
climate-smart
cultivars
adapt
effectively
variation,
meet
consumer
preferences,
address
human
livestock
nutritional
needs.
Most
economically
important
traits
crops
controlled
multiple
loci
often
recessive
alleles.
Considering
particularly
Africa,
continent
has
several
agro-climatic
zones,
hence
need
adapted
these.
Therefore,
targeting
specific
using
modern
tools
offers
precise
approach.
This
review
article
aims
how
new
provide
better
support
Language: Английский
The multifaceted role of microRNA in medicinal plants
Yurong Yang,
No information about this author
Wang Chen,
No information about this author
Zhinan Mei
No information about this author
et al.
Medicinal Plant Biology,
Journal Year:
2025,
Volume and Issue:
4(1), P. 0 - 0
Published: Jan. 1, 2025
Language: Английский
Research on Crop Planting Decision Model Based on Linear Programming and Genetic Algorithm
H. Jiang,
No information about this author
Y. Tian
No information about this author
Highlights in Business Economics and Management,
Journal Year:
2025,
Volume and Issue:
51, P. 283 - 292
Published: Feb. 27, 2025
This
study
presents
an
optimization
of
crop
planting
strategies
for
a
rural
area
in
the
mountainous
region
North
China,
covering
period
from
2024
to
2030,
with
objective
maximizing
profits
amid
resource
constraints
and
market
volatility.
We
employed
linear
programming
model
identify
profit-maximizing
while
incorporating
multiple
constraints.
Utilizing
enhanced
genetic
algorithm,
projected
maximum
53
million
58
yuan
under
different
scenarios.
Furthermore,
we
developed
bi-objective
robust
informed
by
orthogonal
experimental
design,
utilizing
improved
NSGA-II
algorithm
address
uncertainties.
approach
yielded
average
54.4
61
yuan,
minimum
profit
guarantees
54.25
59.5
adverse
conditions,
effectively
managing
risks.
The
findings
provide
framework
optimizing
regions
promoting
economic
growth
sustainable
agricultural
practices
enhancing
decision-making
resilience.
Language: Английский