Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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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 MJIn 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.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 PRSheep (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.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 PRSheep 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.Item Resilience, risk and entrepreneurship(International Food and Agribusiness Management Association, 1/05/2016) Shadbolt NM; Olubode-Awosola FFarmers 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.Item Factors influencing the Dairy Trade from New Zealand(International Food and Agribusiness Management Association, 24/08/2016) Shadbolt NM; Apparao DItem Moringa oleifera L.: A Potential Plant for Greenhouse Gas Mitigation in Temperate Agriculture Systems(Versita, 28/07/2022) Sofkova-Bobcheva SThe earth’s climate is changing because of the increase in greenhouse gas (GHG) concentration, to which livestock is a major contributor. Methane produced from cattle can be reduced by using high quality forages. This study compared the GHG produced from M. oleifera in an artificial ruminant system with two high quality pasture species, ryegrass and white clover. Methane and total gas production were measured using an in vitro batch culture system. A preliminary screening using oven dried M. oleifera planted in field and greenhouse, and a main experiment using six provenances of M. oleifera, a composite sample and M. oleifera leaves from greenhouse was undertaken. Both experiments compared the M. oleifera from different sources with high quality ryegrass and white clover. Real time gas production was recorded for 48 h, total gas production, methane analysed at 12 and 24 h. Short chain fatty acids concentration were also determined at the end of the fermentation. Preliminary results showed that M. oleifera leaves grown in field and greenhouse have lower gas and methane production compared with ryegrass, but similar to white clover. The differences were driven by a high production of propionic and butyric acids. The six M. oleifera provenances also produced less methane than ryegrass but were similar to white clover at 12 and 24 h after the start of fermentation. M. oleifera fermented faster than ryegrass or white clover. Hydrogen production from fermentation of M. oleifera might not have been diverted to methane production but removed by other compounds. In vitro fermentation showed differences in methane production across provenances. This suggests that it may be possible to select for low methane genotypes.Item Linking smallholder producers to high-value markets through producer cooperatives: A case study of vegetable producer cooperatives in Cambodia(International Food and Agribusiness Management Association, 10/02/2021) Tray B; Garnevska E; Shadbolt NModern retail markets have grown in Cambodia, but vegetable growers are unlikely to gain benefits from these high value markets (HVMs). Producer cooperatives (PCs) could play a critical role in linking smallholder farmers to HVMs. The purpose of this paper is: (1) to examine the role of PCs in linking vegetable producers to HVMs; and (2) analyse the factors affecting successful participation in HVMs. This study applied a mixed methods approach to PCs selling the members’ vegetables to HVMs (PC-HVMs), and PCs selling members’ vegetables to traditional markets (TMs) only (PC-TMs). Both groups of PCs provided services to their members (e.g. input, financial, extension services). However, the content and quality of these services were different. PC-TMs emphasised only on support linked to production, while PC-HVMs focused on both production and marketing support. This study indicated that vegetable farming experience, total vegetable produce, and average vegetable prices had a statistically significant influence on producers’ participation in HVMs. However, vegetable farm size showed a negatively significant effect on participation in HVMs. As one of the very few empirical studies on PCs in Cambodia the research provides valuable context for further studies. It has developed and tested a framework for analysing the factors affecting successful participation in HVMs and provides an explanation of why some PCs can successfully participate in HVMs.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 PRBody 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.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 NThe 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.

