Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item Nutrient-Level Evaluation of Meals Provided on the Government-Funded School Lunch Program in New Zealand(MDPI (Basel, Switzerland), 2022-12) de Seymour J; Stollenwerk Cavallaro A; Wharemate-Keung L; Ching S; Jackson J; Maeda-Yamamoto MApproximately 1 in 6 children in New Zealand are living in households facing poverty and 14% of the population is food insecure. The Ka Ora, Ka Ako|Healthy School Lunches program aims to reduce food insecurity by providing access to a nutritious lunch every school day. This study analyzed the nutritional content of Ka Ora, Ka Ako meals and compared them to national and international standards. Meals were selected at random from approved menus. The suppliers covered by the 302 meals analyzed provide 161,699 students with a lunch (74.9% of students on the program). The meals were analyzed using Foodworks 10 nutrient analysis software. The nutrient content was compared against the New Zealand/Australia Nutrient Reference Values (NRVs) and to nutrient-level standards for international school lunch programs. A total of 77.5% of nutrients analyzed exceeded 30% of the recommended daily intakes. Protein, vitamin A and folate met the NRV targets and a majority of the international standards (55/57). Energy, calcium, and iron were low compared to NRVs and international standards (meeting 2/76 standards). Carbohydrates were low compared to international standards. The findings have been used to inform the development of revised nutrition standards for the program, which will be released in 2022.Item Assessing the Leaf Blade Nutrient Status of Pinot Noir Using Hyperspectral Reflectance and Machine Learning Models(MDPI (Basel, Switzerland), 2023-03-08) Lyu H; Grafton M; Ramilan T; Irwin M; Sandoval E; Díaz-Varela RAMonitoring grape nutrient status, from flowering to veraison, is important for viticulturists when implementing vineyard management strategies, in order to produce quality wines. However, traditional methods for measuring nutrient elements incur high labour costs. The aim of this study is to explore the potential of predicting grapevine leaf blade nutrient concentration based on hyperspectral data. Leaf blades were collected at two Pinot Noir commercial vineyards at Martinborough, New Zealand. The leaf blade spectral data were obtained with a handheld spectroradiometer, to evaluate surface reflectance and derivative spectra in the spectrum range between 400 and 2400 nm. Afterwards, leaf blades nutrient concentrations (N, P, K, Ca, and Mg) were measured, and their relationships with the hyperspectral data were modelled by machine learning models; partial least squares regression (PLSR), random forest regression (RFR), and support vector regression (SVR) were used. Pearson correlation and recursive feature elimination, based on cross-validation, were used as feature selection methods for RFR and SVR, to improve the model’s performance. The variable importance score of PLSR, and permutation variable importance of RFR and SVR, were used to determine the most sensitive wavelengths, or spectral regions related to each biochemical variable. The results showed that the best predictive performance for leaf blade N concentration was based on PLSR to raw reflectance data (R2 = 0.66; RMSE = 0.15%). The combination of support vector regression with the Pearson correlation selected method and second derivative reflectance provided a high accuracy for K and Ca modelling (R2 = 0.7; RMSE = 0.06%; R2 = 0.62; RMSE = 0.11%, respectively). However, the modelling performance for P and Mg, by different feature groups and variable selection methods, was poor (R2 = 0.15; RMSE = 0.02%; R2 = 0.43; RMSE = 0.43%, respectively). Thus, a larger dataset is needed for improving the prediction of P and Mg. The results indicated that for Pinot Noir leaf blades, raw reflectance data had potential for the prediction of N concentration, while the second-derivative spectra were more suitable to predict K and Ca. This study led to the provision of rapid and non-destructive measurements of grapevine leaf nutrient status.Item Nutritional needs and health outcomes of ageing cats and dogs: is it time for updated nutrient guidelines?(Oxford University Press on behalf of the American Society of Animal Science, 2024-06-20) Bermingham EN; Patterson KA; Shoveller AK; Fraser K; Butowski CF; Thomas DGImplications • While cats are classed as senior at 10 years of chronological age, physiological and health changes occur from 8 years of age and it appears that diet may influence the ageing process. • Dogs are classed as senior at 12 years for smaller dogs and 10 years for larger breeds. Due to differences in longevity associated with breed size a definite age that dogs start to experience changes is difficult to establish. • Despite our pets ageing, living in extreme cases to 30 + years, there are no explicit nutritional guidelines for feeding ageing animals. Increased scientific knowledge around the specific nutritional requirements of ageing cats and dogs is required. • Many of the underlying physiological processes (e.g., immune function) and age-associated health conditions (e.g., cognitive decline) respond to nutritional intervention. This suggests that nutritional and regulatory guidelines, should consider recommendations for ‘senior+’ pets. • Due to the unique nutritional requirements of cats and dogs, more specific knowledge around the mechanisms of ageing is required.Item The influence of ripening on the nutrient composition and antioxidant properties of New Zealand damson plums(Wiley Periodicals LLC, 2024-03-30) Rashidinejad A; Ahmmed MKThe current study pioneers a comprehensive exploration into the influence of ripening stages on the nutritional composition and antioxidant attributes of the New Zealand damson plums (Prunus domestica ssp. Insititia). Sampled at early-, mid-, and late-ripening stages from randomly selected plum trees, the investigation unveiled notable significant (p <.05) declines in multiple parameters as ripening progressed. Noteworthy reductions in dry matter (from 21% to 19.33%), stone weight (from 30.23% to 24.30%), total dietary fiber (from 3.15% to 2.5%), energy content (from 280 to 263 kJ/100 g), vitamin D3 (from 1.67 to 1.53 μg/100 g), vitamin A (from 4.2 to 3.87 μg/100 g), and specific minerals (e.g., Ca, Mg, and P) emerged as a hallmark of this progression. Additionally, plums harvested at the advanced ripening stage exhibited heightened moisture content in contrast to their early-stage counterparts. Conversely, ash, protein, carbohydrates, total sugar, and minerals (including K, Na, Zn, and Se) demonstrated no significant alteration (p >.05) across ripening stages. Remarkably, damson plums that were harvested at the end of the ripening stage displayed reduced phenolic content and total antioxidant activity compared to those acquired at the early–mid ripening phase. This research collectively highlights the substantive impact of harvesting time and ripening stage on the nutritional and antioxidant profiles of damson plums cultivated in New Zealand.Item Nutrient Dense, Low-Cost Foods Can Improve the Affordability and Quality of the New Zealand Diet-A Substitution Modeling Study(MDPI (Basel, Switzerland), 2021-07-27) Starck CS; Blumfield M; Keighley T; Marshall S; Petocz P; Inan-Eroglu E; Abbott K; Cassettari T; Ali A; Wham C; Kruger R; Kira G; Fayet-Moore FThe high prevalence of non-communicable disease in New Zealand (NZ) is driven in part by unhealthy diet selections, with food costs contributing to an increased risk for vulnerable population groups. This study aimed to: (i) identify the nutrient density-to-cost ratio of NZ foods; (ii) model the impact of substituting foods with a lower nutrient density-to-cost ratio with those with a higher nutrient density-to-cost ratio on diet quality and affordability in representative NZ population samples for low and medium socioeconomic status (SES) households by ethnicity; and (iii) evaluate food processing level. Foods were categorized, coded for processing level and discretionary status, analyzed for nutrient density and cost, and ranked by nutrient density-to-cost ratio. The top quartile of nutrient dense, low-cost foods were 56% unprocessed (vegetables, fruit, porridge, pasta, rice, nuts/seeds), 31% ultra-processed (vegetable dishes, fortified bread, breakfast cereals unfortified <15 g sugars/100 g and fortified 15–30 g sugars/100 g), 6% processed (fruit juice), and 6% culinary processed (oils). Using substitution modeling, diet quality improved by 59% and 71% for adults and children, respectively, and affordability increased by 20–24%, depending on ethnicity and SES. The NZ diet can be made healthier and more affordable when nutritious, low-cost foods are selected. Processing levels in the healthier, modeled diet suggest that some non-discretionary ultra-processed foods may provide a valuable source of low-cost nutrition for food insecure populations.Item Assessing the Leaf Blade Nutrient Status of Pinot Noir Using Hyperspectral Reflectance and Machine Learning Models(MDPI AG, 8/03/2023) Lyu H; Grafton MC; Ramilan T; Irwin M; Sandoval - Cruz E; Díaz-Varela, RA