Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

Browse

Has files: YesSubject: search.filters.subject.0701 Agriculture, Land and Farm Management

Search Results

Now showing 1 - 6 of 6
  • Thumbnail Image
    Item
    Ballistic modeling and pattern testing to prevent separation of New Zealand fertilizer products
    (American Society of Agricultural and Biological Engineers, 18/06/2015) Grafton MCE; Yule IJ; Robertson BG; Chok SM; Manning MJ
    In recent years twin disc centrifugal spreaders have become larger with some manufacturers claiming to be able to spread fertilizer products as far as 60 m. To achieve wider spread widths, the fertilizer particle exit velocity off the disc has increased, as a result the ballistic qualities of the product becomes more critical. This case study uses data-mined information from Ravensdown Fertiliser Co-op Ltd, a major fertilizer supplier. This article examines and researches products used by arable and grassland farmers and studies the effect of changes in product characteristics on spread bout width from these newer spreaders. Ballistic modeling, based on particle density, size, and shape was used to test the distance fertilizer particles travel at various velocities. Fertilizer particle velocities were measured by high speed photometry using both common fertilizers and common spreaders found in New Zealand. Spreading equipment was pattern tested using the New Zealand Spreadmark method. Ballistic modeling of particles proved appropriate in ideal conditions. Fertilizer manufacturers believe that spreader operators often fail to take account of physical characteristics of products being spread and target the widest bout width possible. This can lead to an in-field Coefficient of Variation (CV) which is much greater than 15% and leads to sub-optimal utilization of fertilizer, where variations in particle size distribution occur. Similar situations have been experienced when spreading fertilizer blends; where blends previously spread successfully, at narrower bout widths now separate. Ballistic models could provide bout width recommendations for products and blends, for a range of applicators and reduce crop striping.
  • Thumbnail Image
    Item
    The effect of herbage availability and season of year on the rate of liveweight loss during weighing of fasting ewe lambs
    (1/02/2021) Semakula J; Corner-Thomas RA; Morris ST; Blair HT; Kenyon PR
    Sheep (Ovis aries) liveweight and liveweight change can contain errors when collection procedures are not standardized, or when there are varying time delays between removal from grazing and weighing. A two-stage study was conducted to determine the effect of herbage availability and season of year on the rate of liveweight loss during fasting and to develop and validate correction equations applied to sets of delayed liveweights collected under commercial conditions. Results showed that ewe lambs offered the Low herbage availability lost up to 1.7 kg and those offered the Medium or High herbage availability lost 2.4 kg during 8 h of delayed weighing without access to feed or drinking water. The rate of liveweight loss varied by season, herbage availability and farm (p < 0.05). Applying correction equations on matching liveweight data collected under similar conditions, provided more accurate estimates (33-55%) of without delay liveweight than using the delayed liveweight. In conclusion, a short-term delay prior to weighing commonly associated with practical handling operations significantly reduced the liveweight recorded for individual sheep. Using delayed liveweights on commercial farms and in research can have significant consequences for management practices and research results globally, therefore, liveweight data should be collected without delay. However, when this is not feasible delayed liveweights should be corrected, and in the absence of locally formulated correction equations, the ones presented in this paper could be used.
  • Thumbnail Image
    Item
    The effect of herbage availability, pregnancy stage and rank on the rate of liveweight loss during fasting in ewes
    (1/06/2021) Semakula J; Corner-Thomas RA; Morris ST; Blair HT; Kenyon PR
    Sheep liveweight and liveweight change are vital tools both for commercial and research farm management. However, they can be unreliable when collection procedures are not standardized or when there are varying time delays between sheep removal from grazing and weighing. This study had two stages with different objectives: (1) A liveweight loss study to determine the effect of herbage availability (Low and High) on the rate of liveweight loss of ewes at different pregnancy stages (approximately 100 days of pregnancy: P100 and 130 days: P130) and ranks (single and twin); (2) A follow-up liveweight loss study to develop and validate correction equations for delayed liveweights by applying them to data sets collected under commercial conditions. Results from each stage showed that the rate of liveweight loss varied by herbage availability and stage of pregnancy (p < 0.05) but not pregnancy-rank (p > 0.05). Further, the rate of liveweight loss differed by farm (p < 0.05). Applying liveweight correction equations increased the accuracy of without delay liveweight estimates in P100 ewes by 56% and 45% for single-bearing and twin-bearing ewes, respectively, when offered the Low-level diet. In ewes offered the High-level diet, accuracies of without delay liveweight estimates were increased by 53% and 67% for single-bearing and twin-bearing ewes, respectively. Among P130 ewes, accuracy was increased by 43% and 37% for single-bearing and twin-bearing ewes, respectively, when offered the Low herbage level and by 60% and 50% for single-bearing and twin-bearing ewes, respectively, when offered the High herbage level. In conclusion, a short-term delay of up to 8 hours prior to weighing, which is commonly associated with practical handling operations, significantly reduced the liveweight recorded for individual sheep. Using delayed liveweights on commercial farms and in research can have consequences for management practices and research results; thus, liveweight data should be collected without delay. However, when this is not feasible, delayed ewe liveweights should be corrected and, in the absence of locally devised correction equations, the ones generated in the current study could be applied on farms with similar management conditions and herbage type.
  • Thumbnail Image
    Item
    Resilience, risk and entrepreneurship
    (International Food and Agribusiness Management Association, 1/05/2016) Shadbolt NM; Olubode-Awosola F
    Farmers worldwide face an increasingly turbulent environment. Successful farmers are those that adapt to shifts in the environment to capture the opportunities from such disturbance and outperform those who do not adapt. Such farmers, the literature would suggest, are entrepreneurs, catalysts for change with a risk-taking propensity. The paper presents analysis of farmers grouped with respect to their attitude to risk. It identifies that those farmers that are risk seekers would be more accurately described as gamblers based on their performance over six years of volatility. The most successful group of farmers were risk neutral, had a strong business focus and skills, managing quite high levels of debt to good effect. They had a positive attitude to change and an ability to successfully adapt to changing conditions so best fit the broader definition of entrepreneur. The risk averse group carried less debt and also outperformed the risk seeking group with strong cash results and retained earnings. Farmers cannot be assumed to be successful catalysts for change just from their attitude to risk and a belief in their ability to manage risk; instead they are those whose results prove that they are successfully taking risks, have strong business skills and run efficient farm businesses.
  • Thumbnail Image
    Item
    Application of machine learning algorithms to predict body condition score from liveweight records of mature romney ewes
    (1/02/2021) Semakula J; Corner‐thomas RA; Morris ST; Blair HT; Kenyon PR
    Body condition score (BCS) in sheep (Ovis aries) is a widely used subjective measure of the degree of soft tissue coverage. Body condition score and liveweight are statistically related in ewes; therefore, it was hypothesized that BCS could be accurately predicted from liveweight using machine learning models. Individual ewe liveweight and body condition score data at each stage of the annual cycle (pre‐breeding, pregnancy diagnosis, pre‐lambing and weaning) at 43 to 54 months of age were used. Nine machine learning (ML) algorithms (ordinal logistic regression, multinomial regression, linear discriminant analysis, classification and regression tree, random forest, k‐nearest neighbors, support vector machine, neural networks and gradient boosting decision trees) were applied to predict BCS from a ewe’s current and previous liveweight record. A three class BCS (1.0– 2.0, 2.5–3.5, > 3.5) scale was used due to high‐class imbalance in the five‐scale BCS data. The results showed that using ML to predict ewe BCS at 43 to 54 months of age from current and previous liveweight could be achieved with high accuracy (> 85%) across all stages of the annual cycle. The gradient boosting decision tree algorithm (XGB) was the most efficient for BCS prediction regardless of season. All models had balanced specificity and sensitivity. The findings suggest that there is potential for predicting ewe BCS from liveweight using classification machine learning algorithms.
  • Thumbnail Image
    Item
    Towards high value markets: a case study of smallholder vegetable farmers in Indonesia
    (International Food and Agribusiness Management Association, 27/09/2017) Maspaitella M; Garnevska E; Siddique MI; Shadbolt N
    The expansion of modern markets has significant implications for agriculture in many developing countries that provides both opportunities and challenges for smallholder farmers. The purpose of this paper is to analyse key determinants affecting farmers’ participation in high value markets, compared to traditional market. Face to face interviews based on a questionnaire were conducted with a sample of 126 smallholder vegetable farmers in the Manokwari region. Binary logistic regression and bivariate correlation analysis were used in this study. The results suggested that age, education level, vegetables cultivated area and membership in farmer groups/cooperatives were the key determinants that had significant effects on the smallholder farmers’ decision about marketing channel participation. In addition, the income generated from vegetable farming was positively correlated to high value market participation. Some implications that need to be prioritized in agricultural development strategies include improving technical innovations and empowering collective actions through cooperatives or farmer groups.