Inference of the genetic basis of fruit texture in highbush blueberries using genome-wide association analyses.

The global production and consumption of blueberry ( spp.), a specialty crop known for its abundant bioactive and antioxidant compounds, has more than doubled over the last decade. To hold this momentum, plant breeders have begun to use quantitative genetics and molecular breeding to guide their decisions and select new cultivars that are improved for fruit quality.

Dissecting the genetic basis of bioactive metabolites and fruit quality traits in blueberries ( L.).

Blueberry is well-recognized as a healthy fruit with functionality derived largely from anthocyanin and chlorogenic acid. Despite their importance, no study to date has evaluated the genetic basis of these bioactives in blueberries and their relationship with fruit quality traits. Hence, to fill this gap, a mapping population including 196 F individuals was phenotyped for anthocyanin and chlorogenic acid concentration and fruit quality traits (titratable acidity, pH, and total soluble solids) over 3 years and data were used for QTL mapping and correlation analysis.

There and back again; historical perspective and future directions for breeding and research studies.

The genus L. (Ericaceae) contains a wide diversity of culturally and economically important berry crop species. Consumer demand and scientific research in blueberry ( spp.

Non- Staphylococci and Bovine Udder Health: Current Understanding and Knowledge Gaps.

Despite considerable efforts to control bovine mastitis and explain its causes, it remains the most costly and common disease of dairy cattle worldwide. The role and impact of non- staphylococci (NAS) in udder health are not entirely understood. These Gram-positive bacteria have become the most frequently isolated group of bacteria in milk samples of dairy cows and are associated with (mild) clinical and subclinical mastitis.

Factors associated with the adoption of technologies by the Canadian dairy industry.

Data generated from Statistics Canada's 2016 Census of Agriculture and Census of Population were used to describe the adoption of 8 technologies by the Canadian dairy industry: computer/laptop, smartphone/tablet, auto-steering, auto-feeding, auto-environment, robotic milking, global positioning systems (GPS), and geographical information systems (GIS). Logistic regression was used to analyze the adoption of each technology by geographical region, operators' gender, operators' age, herd size, and number of operators per farm. Gender and age were marginally related to the level of adoption of each technology, whereas the number of operators per dairy farm and farm size were associated with increased adoption of most technologies.