S.M. Sinton

ORCID: 0000-0001-6625-0449
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About
Contact & Profiles
Research Areas
  • Potato Plant Research
  • Phytochemical Studies and Bioactivities
  • Plant Disease Resistance and Genetics
  • Plant Pathogens and Resistance
  • Ruminant Nutrition and Digestive Physiology
  • Plant nutrient uptake and metabolism
  • Soil Carbon and Nitrogen Dynamics
  • Greenhouse Technology and Climate Control
  • Irrigation Practices and Water Management
  • Climate change impacts on agriculture
  • Smart Agriculture and AI
  • Phytochemicals and Antioxidant Activities
  • Crop Yield and Soil Fertility
  • Soil and Unsaturated Flow
  • Plant responses to elevated CO2
  • Plant Disease Management Techniques
  • Cynara cardunculus studies
  • Rice Cultivation and Yield Improvement
  • Bioenergy crop production and management
  • Phytochemistry and Bioactive Compounds
  • Landfill Environmental Impact Studies
  • Phytochemical and Pharmacological Studies
  • Powdery Mildew Fungal Diseases
  • Sugarcane Cultivation and Processing
  • Tree-ring climate responses

Plant & Food Research
2011-2022

Changes in soil physical conditions can have an impact on plant root growth. However, the underlying functional responses of growth to variations properties still remain poorly understood. We assessed barley (Hordeum vulgare L.) roots a typical range created by applying different degrees loosening or compaction subsurface layers. A replicated field experiment was established Templeton silt loam (Dystric Ustochrept) Canterbury, New Zealand. Following removal top 15 cm soil, five mechanical...

10.2136/sssaj2014.01.0005 article EN Soil Science Society of America Journal 2014-06-30

The physiology of yield determination in asparagus (Asparagus officinalis L.) is complex. Above-ground growth spears and ferns the ultimate indicator performance. However, driven by soluble carbohydrate (CHO), which has a well-known pattern gain loss storage root system during crop’s annual cycle. Root CHO content better performance indicator, now that relationship between above-ground changes understood. Recent research improved definition pattern, benchmark contents at key times Detection...

10.17660/actahortic.2008.776.54 article EN Acta Horticulturae 2008-01-01

Leaf intrinsic water-use efficiency (WUE), the ratio of photosynthetic rate to stomatal conductance (A/g(s) ), is a key plant trait linking terrestrial carbon and water cycles. A rapid, integrative proxy for A/g(s) benefit crop breeding programmes aiming improve WUE, but also ecologists interested in carbon-water balance natural systems. We hypothesize that isotope composition leaf-respired CO(2) (δ(13) C(Rl) two hours after leaves are transferred dark, records discrimination so provides ....

10.1111/j.1365-3040.2011.02282.x article EN Plant Cell & Environment 2011-01-28

Changes in soil physical properties due to compaction are a major concern agricultural production and modeling of water movement plant growth. The objectives this study were measure infiltration under different levels characterize the effects on soil's porosity its associated water-conducting properties. On silt loam soil, relative control, four subsurface induced: loosening light, medium, heavy compaction. Infiltration characteristics measured situ using tension infiltrometers....

10.2136/sssaj2010.0257 article EN Soil Science Society of America Journal 2011-05-01

10.17660/actahortic.2002.589.40 article EN Acta Horticulturae 2002-10-01

Abstract In New Zealand, potato crop yields of 90 t ha −1 are achievable but at 55 , the average is becoming economically unsustainable. 2012/13, a grower-initiated survey found that Rhizoctonia solani and Spongospora subterranea (soil-borne pathogens) soil compaction were widespread in 11 Canterbury crops. Targeted areas these crops had measured yield losses 0 (healthy plants) – 42 (diseased, resource constrained limiting farmer-measured field to 56 average. 2014/15, growth, water use...

10.1007/s12230-022-09864-5 article EN cc-by American Journal of Potato Research 2022-03-17

Abstract Dynamic, deterministic agricultural models, and current machine learning technologies based on sensor data, enable support decision making for on‐farm management. However, their predictions are subject to various sources of uncertainty. Hybrid analytics that leverage both modelled data provide predictive information makes the best approaches in a timely fashion inform operational inclusive uncertainty quantification. We describe evaluate probabilistic Bayesian assimilation tool...

10.1002/agj2.20659 article EN Agronomy Journal 2021-03-22

10.17660/actahortic.1996.415.47 article EN Acta Horticulturae 1996-04-01

10.17660/actahortic.2008.776.14 article EN Acta Horticulturae 2008-01-01
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