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    Predicting spatiotemporal yield variability to aid arable precision agriculture in New Zealand : a case study of maize-grain crop production in the Waikato region : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Agriculture and Horticulture at Massey University, Palmerston North, New Zealand
    (Massey University, 2020) Jiang, Guopeng
    Precision agriculture attempts to manage within-field spatial variability by applying suitable inputs at the appropriate time, place, and amount. To achieve this, delineation of field-specific management zones (MZs), representing significantly different yield potentials are required. To date, the effectiveness of utilising MZs in New Zealand has potentially been limited due to a lack of emphasis on the interactions between spatiotemporal factors such as soil texture, crop yield, and rainfall. To fill this research gap, this thesis aims to improve the process of delineating MZs by modelling spatiotemporal interactions between spatial crop yield and other complementary factors. Data was collected from five non-irrigated field sites in the Waikato region, based on the availability of several years of maize harvest data. To remove potential yield measurement errors and improve the accuracy of spatial interpolation for yield mapping, a customised filtering algorithm was developed. A supervised machine-learning approach for predicting spatial yield was then developed using several prediction models (stepwise multiple linear regression, feedforward neural network, CART decision tree, random forest, Cubist regression, and XGBoost). To provide insights into managing spatiotemporal yield variability, predictor importance analysis was conducted to identify important yield predictors. The spatial filtering method reduced the root mean squared errors of kriging interpolation for all available years (2014, 2015, 2017 and 2018) in a tested site, suggesting that the method developed in R programme was effective for improving the accuracy of the yield maps. For predicting spatial yield, random forest produced the highest prediction accuracies (R² = 0.08 - 0.50), followed by XGBoost (R² = 0.06 - 0.39). Temporal variables (solar radiation, growing degree days (GDD) and rainfall) were proven to be salient yield predictors. This research demonstrates the viability of these models to predict subfield spatial yield, using input data that is inexpensive and readily available to arable farms in New Zealand. The novel approach employed by this thesis may provide opportunities to improve arable farming input-use efficiency and reduce its environmental impact.
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    New sensing methods for scheduling variable rate irrigation to improve water use efficiency and reduce the environmental footprint : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Soil Science at Massey University, Palmerston North, New Zealand
    (Massey University, 2020) El-Naggar, Ahmed
    Irrigation is the largest user of allocated freshwater, so conservation of water use should begin with improving the efficiency of crop irrigation. Improved irrigation management is necessary for humid areas such as New Zealand in order to produce greater yields, overcome excessive irrigation and eliminate nitrogen losses due to accelerated leaching and/or denitrification. The impact of two different climatic regimes (Hawkes Bay, Manawatū) and soils (free and imperfect drainage) on irrigated pea (Pisum sativum., cv. ‘Ashton’) and barley (Hordeum vulgare., cv. ‘Carfields CKS1’) production was investigated. These experiments were conducted to determine whether variable-rate irrigation (VRI) was warranted. The results showed that both weather conditions and within-field soil variability had a significant effect on the irrigated pea and barley crops (pea yield - 4.15 and 1.75 t/ha; barley yield - 4.0 and 10.3 t/ha for freely and imperfectly drained soils, respectively). Given these results, soil spatial variability was characterised at precision scales using proximal sensor survey systems: to inform precision irrigation practice. Apparent soil electrical conductivity (ECa) data were collected by a Dualem-421S electromagnetic (EM) survey, and the data were kriged into a map and modelled to predict ECa to depth. The ECa depth models were related to soil moisture (θv), and the intrinsic soil differences. The method was used to guide the placement of soil moisture sensors. After quantifying precision irrigation management zones using EM technology, dynamic irrigation scheduling for a VRI system was used to efficiently irrigate a pea crop (Pisum sativum., cv. ‘Massey’) and a French bean crop (Phaseolus vulgaris., cv. ‘Contender’) over one season at the Manawatū site. The effects of two VRI scheduling methods using (i) a soil water balance model and (ii) sensors, were compared. The sensor-based technique irrigated 23–45% less water because the model-based approach overestimated drainage for the slower draining soil. There were no significant crop growth and yield differences between the two approaches, and water use efficiency (WUE) was higher under the scheduling regime based on sensors. ii To further investigate the use of sensor-based scheduling, a new method was developed to assess crop height and biomass for pea, bean and barley crops at high field resolution (0.01 m) using ground-based LiDAR (Light Detection and Ranging) data. The LiDAR multi-temporal, crop height maps can usefully improve crop coefficient estimates in soil water balance models. The results were validated against manually measured plant parameters. A critical component of soil water balance models, and of major importance for irrigation scheduling, is the estimation of crop evapotranspiration (ETc) which traditionally relies on regional climate data and default crop factors based on the day of planting. Therefore, the potential of a simpler, site-specific method for estimation of ETc using in-field crop sensors was investigated. Crop indices (NDVI, and canopy surface temperature, Tc) together with site-specific climate data were used to estimate daily crop water use at the Manawatū and Hawkes Bay sites (2017-2019). These site-specific estimates of daily crop water use were then used to evaluate a calibrated FAO-56 Penman-Monteith algorithm to estimate ETc from barley, pea and bean crops. The modified ETc–model showed a high linear correlation between measured and modelled daily ETc for barley, pea, and bean crops. This indicates the potential value of in-field crop sensing for estimating site-specific values of ETc. A model-based, decision support software system (VRI–DSS) that automates irrigation scheduling to variable soils and multiple crops was then tested at both the Manawatū and Hawkes Bay farm sites. The results showed that the virtual climate forecast models used for this study provided an adequate prediction of evapotranspiration but over predicted rainfall. However, when local data was used with the VRI–DSS system to simulate results, the soil moisture deficit showed good agreement with weekly neutron probe readings. The use of model system-based irrigation scheduling allowed two-thirds of the irrigation water to be saved for the high available water content (AWC) soil. During the season 2018 – 2019, the VRI–DSS was again used to evaluate the level of available soil water (threshold) at which irrigation should be applied to increase WUE and crop water productivity (WP) for spring wheat (Triticum aestivum L., cv. ‘Sensas’) on the sandy loam and silt loam soil zones at the Manawatū site. Two irrigation thresholds (40% and 60% AWC), were investigated in each soil zone along with a rainfed control. Soil water uptake pattern was affected mainly by the soil type rather than irrigation. The soil iii water uptake decreased with soil depth for the sandy loam whereas water was taken up uniformly from all depths of the silt loam. The 60% AWC treatments had greater irrigation water use efficiency (IWUE) than the 40% AWC treatments, indicating that irrigation scheduling using a 60% AWC trigger could be recommended for this soil-crop scenario. Overall, in this study, we have developed new sensor-based methods that can support improved spatial irrigation water management. The findings from this study led to a more beneficial use of agricultural water.
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    The environmental ethics of the corporatization of agriculture and crop genetic engineering : a thesis presented in partial fulfilment of the requirements for the degree of Master of Environmental Management at Massey University, Palmerston North, New Zealand
    (Massey University, 2017) Walker, Anna
    The corporatization of agriculture has resulted in significant implications for the environment and consequently environmental management. In particular, corporate application of genetic engineering (GE) has resulted in increased and unnecessary environmental risks through inappropriate applications of GE and increased pesticide use. GE technology has in turn allowed for the agriculture industry to become further corporatized. Current environmental management procedures with regard to risk assessment and the regulatory processes of GE crops have proven inadequate in light of such corporate involvement. The research aim of this thesis was to establish whether the corporatization of agriculture, and the consequent corporate application of GE crops, results in breaches of environmental ethics, as defined by the worldviews of biocentrism and ecocentrism. This aim was achieved through the application of a structured literature review, using an interpretive approach within the paradigm of hermeneutics. The literature analysis was carried out on peer-reviewed journal articles from the last 10 year period, within which selected articles were asked a series of interview questions in order to fulfil the research objectives, and consequently the aim. The extracted information was critically considered within the framework of environmental ethics and the contrasting worldviews of anthropocentrism, technocentrism, biocentrism and ecocentrism. The key issue identified was the lack of consideration of biocentric and ecocentric values in the arguments made by corporations and proponents of GE crops as a result of a dominance of anthropocentric and technocentric worldviews. The lack of such values on the part of corporations ensures that both sides of the debate are arguing from different perspectives and as such it seems unlikely that they will ever be able to reach a resolution. This thesis concludes that for progress to be made in the debate on GE agriculture and corporatization, and for appropriate precaution to be employed with regard to risk assessment, the worldview held by agrochemical corporations and proponents of GE needs to shift towards a biocentric and ecocentric understanding of the environment. However, as a complete shift of worldviews on the part of corporations is unlikely, this thesis recommends that attention be shifted away from the polarized controversy in favour of a discussion on coexistence.
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    Genetic engineering and organic agriculture : perceptions of organice exporters, producers, and consumers : a thesis presented in partial fulfillment of the requirements for the degree of Master of Applied Science in Natural Resource Management
    (Massey University, 2000) Wreford, Anita Barbara
    Genetic engineering technology is becoming increasingly widespread throughout the world. Since the late 1990s there has been intense controversy regarding its use in food production. Organic agriculture could lose or gain significantly from consumer uncertainty and apprehension regarding the genetic engineering of food products. Concerns about genetic engineering spread across the world, and organic agriculture is in a strong position to exploit consumer concerns about genetically engineered food. However, organic farming is also at risk from the cross-contamination of engineered crops, pest-resistance exacerbated by the technology, and the corruption of organic seedlines. In addition, there has been debate as to whether organic standards should be altered to permit the use of genetically engineered crops. This study attempts to gauge the attitudes of three key sectors of the organic industry in New Zealand towards genetic engineering, namely producers, exporters and consumers of organic food in New Zealand. Producers of organic food in New Zealand were questioned regarding their views on genetic engineering, and whether they would consider incorporating genetically engineered crops in their food production. Exporters of New Zealand organic produce were questioned on the international organic markets and the exporters own opinions of consumer concerns towards genetically engineered food. Consumers of organic food were surveyed on their attitudes and beliefs about genetic engineering, and the possibility of genetically engineered organic food. Results for each survey sample were analysed using the statistical package SPSS. The results show conclusively that organic exporters, producers and consumers do not want to eat or grow genetically engineered organic food. This appears to be based on intrinsic and ethical concerns as much as environmental and health concerns. Even if reassured about the safety of genetically engineered food to the environment and to human health, most organic consumers claim they would not eat it. It is concluded that there is no future for genetic engineering in the organic industry. The industry would be wise to take advantage of the general consumer unease towards genetic engineering. Research into alternative methods of pest control would also be advised. Keywords: Organic agriculture, Genetic engineering, Genetically modified organism, Consumer perception.