A comparison of crop data measured by two commercial sensors for variable-rate nitrogen application

Nitrogen (N) fertilizer rates applied spatially according to crop requirements can improve the efficiency of N use. The study compares the performance of two commercial sensors, the Yara N-Sensor/FieldScan (Yara International ASA, Germany) and the GreenSeeker (NTech Industries Inc., Ukiah, California, USA), for assessing the status of N in spring wheat (Triticum aestivum L.) and corn (Zea mays L.). Four experiments were conducted at different locations in Quebec and Ontario, Canada. The normalized difference vegetation index (NDVI) was determined with the two sensors at specific growth stages. The NDVI values derived from Yara N-Sensor/FieldScan correlated with those from GreenSeeker, but only at the early growth stages, where the NDVI values varied from 0.2 to 0.6. Both sensors were capable of describing the N condition of the crop or variation in the stand, but each sensor had its own sensitivity characteristics. It follows that the algorithms developed with one sensor for variable-rate N application cannot be transferred directly to another sensor. The Yara N-Sensor/FieldScan views the crop at an oblique angle over the rows and detects more biomass per unit of soil surface compared to the GreenSeeker with its nadir (top-down) view of the crop. The Yara N-Sensor/FieldScan should be used before growth stage V5 for corn during the season if NDVI is used to derive crop N requirements. GreenSeeker performed well where NDVI values were >0.5. However, unlike GreenSeeker, the Yara N-Sensor/FieldScan can also record spectral information from wavebands other than red and near infrared, and more vegetation indices can be derived that might relate better to N status than NDVI.     

Detection of Genetically Modified Soy in Doughs and Cookies

In many countries, including the European Union member states, Switzerland, Australia, New Zealand, and Japan, legislation has been set up for labeling of genetically modified organisms (GMOs) in food and feed products. To comply with these regulations, reliable detection methods are necessary. If the detection is based on DNA, a GMO analysis may contain several steps where qualitative and quantitative species-specific, GMO screening, GMO construct, and GMO line-specific polymerase chain reactions (PCRs) are used. A limit of detection (LOD) thereby defines to what extent a target molecule may be detected in a sample. In this study, cookies were made with variable levels of a soy sample containing 2 wt% Roundup Ready soy. For all PCRs described, detection limits based on dilution series and practical LODs were determined. The practical LODs are used to determine to what extent a GMO ingredient may be detected in a real food product. Results reveal that, due to the baking process, the overall DNA fragment length is reduced, rendering GMO analyses more difficult. Furthermore, Roundup Ready soy line-specific and real-time quantitative PCR are less sensitive than GMO screening PCRs, whereas just these PCRs are crucial in the decision-making process regarding the presence of GMOs in a food product. Moreover, high standard deviations and errors render the precise quantification of GMOs difficult.     

Identifying risk factors for European stone fruit yellows from a survey

ABSTRACT European stone fruit yellows (ESFY) is becoming a major economic problem for Prunus growers in Europe. The causal agent ("Candidatus Phytoplasma prunorum") and its vector (Cacopsylla pruni) have been identified, but the present knowledge of the risk factors for this disease relies, at best, on specific experiments. To assess the relative significance of several factors correlated with ESFY incidence in the field, an exhaustive survey was performed on apricot and Japanese plum orchards in the Crau plain (France). After a preliminary multivariate exploration of the data, we used a logistic regression model to analyze and predict the cumulative number of diseased trees on the basis of a set of quantitative (age, planting density, and area of the orchard) and categorical variables (species, cultivar, and rootstock). Because of the nature of the data, we used an overdispersed binomial model and we developed a parametric bootstrap procedure based on the beta-binomial distribution to obtain confidence intervals. Our results indicated that the age, species, and cultivar of the scion were the major factors explaining the observed number of diseased trees. The planting density and the rootstocks used in the zone under study were less significant, and the area of the orchard had no effect. The residuals of the model showed that some explanatory variables had not been taken into account, because part of the remaining variability could be explained by a grower effect. The spatial distribution of the residuals suggested that one of the reasons for this grower effect was the correlation between orchards closer than 100 m, possibly caused by the flight behavior of infectious vectors.     

Psittacid alphaherpesvirus 5 infection in Indian ringneck parakeets in southern California

Four Indian ringneck parakeets (Psittacula krameri; syn. ringneck parrots or rose-ringed parakeets) were submitted by 2 private owners for autopsy following a history of dyspnea and death. Gross findings were varied and included thickening of the left caudal thoracic air sac, white spots throughout the liver, mild dilation of the proventriculus, coelomic effusion, splenomegaly, and pulmonary congestion and edema. Microscopically, the submitted parakeets had significant lesions in the lower respiratory tract, including necrotizing bronchitis, parabronchitis, and interstitial pneumonia with numerous syncytia containing eosinophilic intranuclear inclusions. Electron microscopy of the lungs was compatible with a herpesviral infection and Psittacid alphaherpesvirus 5 (PsAHV5) was detected via PCR and sequencing. There has been inconsistent terminology used with Psittacid alphaherpesvirus 3 and PsAHV5; we attempt here to clarify the reported history of these viruses.     

Issues and challenges in landscape models for agriculture: from the representation of agroecosystems to the design of management strategies

Context

Agroecosystems produce food and many other services that are crucial for human well-being. Given the scales at which the processes underlying these services take place, agricultural landscapes appear as appropriate spatial units for their evaluation and management. The design of sustainable agricultural landscapes that value these services has thus become a pressing issue but faces major challenges stemming from the diversity of processes, their interactions and the number of scales at stake. Agricultural landscape modelling can provide a key contribution to this design but must still overcome several difficulties to offer reliable tools for decision makers.

Objectives

Our study aimed at shedding light on the main scientific and technical difficulties that make the building of landscape models that may efficiently inform decision-makers a complex task, as well as translating them in terms of challenges that can be further investigated and discussed.

Methods

We examine current issues and challenges and indicate future research needs to overcome the scientific and technical obstacles in the development of useful agricultural landscape models.

Results

We highlight research perspectives to better couple landscape patterns and process models and account for feedbacks, integrate the decisions of multiple stakeholders, consider the spatial and temporal heterogeneity of data and processes, explore alternative landscape organisations and assess multiobjective performance.

Conclusion

Coping with the issues and challenges discussed in this paper should improve our understanding of agroecosystems and give rise to new hypotheses, thereby informing future research.

     

Idiopathic polyradiculoneuropathy in a Bengal cat: electrophysiological findings and 1 year follow-up

This report describes a rapidly progressive loss of motor function in a 16-month-old male neutered Bengal cat, beginning in the pelvic limbs and progressing to involve all limbs and rendering the cat non-ambulatory. The neurological examination revealed flaccid tetraparesis with decreased spinal reflexes but preserved conscious proprioception and skin sensation. Extensive electrophysiological tests were conducted including electromyography, motor and sensory peripheral nerves potential recordings and 'late' potentials, defining the electrodiagnostic characteristics of this disease. Based on the electrophysiological findings, a generalised proximal and predominantly axonal neuropathy affecting the ventral (motor) nerve roots was suspected. As no aetiology was identified, this disease was classified as idiopathic polyradiculoneuropathy. Over a year, the cat presented three separate episodes of tetraparesis, each with a spontaneous complete recovery, consistent with the reportedly good prognosis for this disease.     

Inferring the effects of landscape structure on roe deer (Capreolus capreolus) movements using a step selection function

In this study, we sought to understand how landscape structure affects roe deer movements within their home-range in a heterogeneous and fragmented agricultural system of south-western France. We analysed the movements of 20 roe deer fitted with GPS collars which recorded their locations every 2–6 h over several months (mean = 9 months). Based on empirical observations and previous studies of roe deer habitat use, we hypothesised that roe deer should avoid buildings and roads, move preferentially along valley bottoms and through the more wooded areas of the landscape. To test these hypotheses we paired each observed movement step with 10 random ones. Using conditional logistic regression, we modelled a step selection function, which represents the probability of selecting a given step as a function of these landscape variables. The selected model indicated that movements were influenced by all the tested landscape features, but not always in the predicted direction: our results suggested that roe deer tend to avoid buildings, roads, valley bottoms and possibly the more wooded areas (although the latter result should be interpreted with caution, as it may be influenced by a bias in the rate of GPS fix acquisition in woods). The distances to buildings and to roads were the most influential variables in the model, suggesting that the avoidance of potential sources of disturbance may be a key factor in determining ranging behaviour of roe deer in human dominated landscapes.     

Diversity of leaf traits related to productivity in 31 Populus deltoides x Populus nigra clones

To test if some leaf parameters are predictors of productivity in a range of Populus deltoides (Bartr.) Marsh. x P. nigra L. clones, we assessed leaf traits and productivity in 2-month-old rooted cuttings from 31 clones growing in 4-l pots in a greenhouse, under conditions of controlled temperature and optimal irrigation. We evaluated four groups of variables describing (1) productivity (total biomass), (2) leaf growth (total leaf number increment and total leaf area increment rate), (3) leaf structure (specific leaf area and nitrogen and carbon contents) and (4) carbon isotope discrimination (delta), which is negatively correlated with time-integrated water-use efficiency. High-yielding clones did not necessarily display high leaf growth rates, but they displayed a larger total leaf area, lower specific leaf area and lower leaf nitrogen concentration than clones with low productivity. Total leaf area was mainly controlled by maximal individual leaf area and total leaf area increment rate (r = 0.51 and 0.56, respectively). Carbon isotope discrimination did not correlate with total biomass, but it was associated with total number of leaves and total leaf area increment rate (r = 0.39 and 0.45, respectively). Therefore, leaf area and specific leaf area were better indicators of productivity than leaf growth traits. The observed independence of delta from biomass production provides opportunities for selecting poplar clones combining high productivity and high water-use efficiency.     

Effects of crown development on leaf irradiance,leaf morphology and photosynthetic capacity in a peach tree

The three-dimensional (3-D) architecture of a peach tree (Prunus persica L. Batsch) growing in an orchard near Avignon, France, was digitized in April 1999 and again four weeks later in May 1999 to quantify increases in leaf area and crown volume as shoots developed. A 3-D model of radiation transfer was used to determine effects of changes in leaf area density and canopy volume on the spatial distribution of absorbed quantum irradiance (PAR(a)). Effects of changes in PAR(a) on leaf morphological and physiological properties were determined. Leaf mass per unit area (M(a)) and leaf nitrogen concentration per unit leaf area (N(a)) were both nonlinearly related to PAR(a), and there was a weak linear relationship between leaf nitrogen concentration per unit leaf mass (N(m)) and PAR(a). Photosynthetic capacity, defined as maximal rates of ribulose-1,5-bisphosphate carboxylase (Rubisco) carboxylation (V(cmax)) and electron transport (J(max)), was measured on leaf samples representing sunlit and shaded micro-environments at the same time that the tree crown was digitized. Both V(cmax) and J(max) were linearly related to N(a) during May, but not in April when the range of N(a) was low. Photosynthetic capacity per unit N(a) appeared to decline between April and May. Variability in leaf nitrogen partitioning between Rubisco carboxylation and electron transport was small, and the partitioning coefficients were unrelated to N(a). Spatial variability in photosynthetic capacity resulted from acclimation to varying PAR(a) as the crown developed, and acclimation was driven principally by changes in M(a) rather than the amount or partitioning of leaf nitrogen.