Bayesian methods for predicting LAI and soil water content

LAI of winter wheat (Triticum aestivum L.) and soil water content of the topsoil (200 mm) and of the subsoil (500 mm) were considered as state variables of a dynamic soil-crop system. This system was assumed to progress according to a Bayesian probabilistic state space model, in which real values of LAI and soil water content were daily introduced in order to correct the model trajectory and reach better future evolution. The chosen crop model was mini STICS which can reduce the computing and execution times while ensuring the robustness of data processing and estimation. To predict simultaneously state variables and model parameters in this non-linear environment, three techniques were used: extended Kalman filtering (EKF), particle filtering (PF), and variational filtering (VF). The significantly improved performance of the VF method when compared to EKF and PF is demonstrated. The variational filter has a low computational complexity and the convergence speed of states and parameters estimation can be adjusted independently. Detailed case studies demonstrated that the root mean square error of the three estimated states (LAI and soil water content of two soil layers) was smaller and that the convergence of all considered parameters was ensured when using VF. Assimilating measurements in a crop model allows accurate prediction of LAI and soil water content at a local scale. As these biophysical properties are key parameters in the crop-plant system characterization, the system has the potential to be used in precision farming to aid farmers and decision makers in developing strategies for site-specific management of inputs, such as fertilizers and water irrigation.     

Influence of source and concentrations of dietary fiber on in vivo nitrogen excretion pathways in pigs as reflected by in vitro fermentation and nitrogen incorporation by fecal bacteria

The inclusion of dietary fiber (DF) in diets has been suggested as a way to reduce NH(3) emission in pig barns because it contributes to a shift in N excretion from urine to feces owing to enhanced bacterial growth in the intestines. This study compared an in vitro method to measure bacterial protein synthesis during fermentation with an in vivo N excretion shift induced by diets differing in DF concentrations and solubility. The first experiment measured the effect of graded concentrations of sugar beet pulp (SBP; 0, 10, 20, and 30%) in corn- and soybean meal-based diets on in vivo N excretion partitioning between the urine and feces. A second experiment investigated the replacement of SBP, rich in soluble DF, with oat hulls (OH), rich in insoluble DF (20:0, 10.5:10.5, and 0:22%, respectively). In parallel, the fermentation characteristics of the dietary carbohydrates not digested in the small intestine were evaluated in an in vitro gas test, based on their incubation with colonic microbiota, using a mineral buffer solution enriched with (15)N. The N originating from the buffer solution incorporated into the bacterial proteins (BNI) was measured when half the final gas volume was produced (8.5 to 14.5 h of fermentation) and after 72 h of fermentation. Short-chain fatty acids were determined in the liquid phase. In the first experiment, the inclusion of SBP linearly decreased urinary N excretion from 0.285 to 0.215 g of N excreted in the urine per gram of N ingested and decreased the urinary-N:fecal-N excretion ratio from 2.171 to 1.177 (P < 0.01). In the second experiment, substituting SBP with OH linearly increased the urinary-N:fecal-N excretion ratio (P = 0.009). Unlike short-chain fatty acid production, BNI was greater at half-time to asymptotic gas production than at 72 h of fermentation. Sugar beet pulp enhanced BNI linearly (P < 0.001), 2.01, 2.06, and 2.35 mg g(-1) of diet with 10, 20, and 30% SBP, respectively, as compared with 1.51 mg for the control diet. The substitution of SBP with OH decreased BNI (P < 0.01). With the exception of final gas production, all in vitro kinetic characteristics and BNI were correlated with in vivo N excretion parameters, and regression equations for the prediction of N excretion pathways from in vitro data were identified. Even if the presence of resistant starch in the diet might alter the composition of the fibrous residue that is fermented, the in vitro method is a possible useful tool for the formulation of diets, reducing the effects of pig production on the environment.     

RTDrift: A real time model for estimating spray drift from ground applications

A spray drift model called RTDrift was developed to estimate drift caused by ground sprayer machines. The sprayer was equipped with sensors measuring operational parameters namely spray pressure, boom height and movements, and geolocalisation. Climatic parameters, including wind speed and direction, were measured using a 2-D ultrasonic anemometer mounted on the sprayer. The nozzles spray drop size spectra were characterised using Phase Doppler Interferometer measurements. At every successive boom position, a diffusion-advection Gaussian tilted plume model computed the spray drift deposits for each drop class taking into account evaporation. The contribution of a single nozzle was calculated by integration of the individual puffs with respect to time and summation of the contributions of individual drops classes. The overall drift generated by the sprayer machine was obtained adding the contributions of all the nozzles. Field trials were performed on a fallow field with water and on crops with pesticides in various wind conditions. The ground drift was measured at different drift distances using fluorometric methods. When comparing the results of the model with experimental measurements of deposits, the model produced realistic maps of drift deposits. Some further improvement is needed in the presence of large scale eddies. The model offers potential benefits for the farmer as a real time drift estimator embedded on a sprayer machine.     

Respiration of three Belgian crops: Partitioning of total ecosystem respiration in its heterotrophic, above- and below-ground autotrophic components

An experimental system combining an eddy covariance system, a micrometeorological station and soil chambers placed in planted areas and in root exclusion zones was installed during three successive years in a production crop managed in a traditional way at the Lonzée experimental site (Belgium). Measurements were made successively on seed potato, winter wheat and sugar beet. The general objectives of the study were, first to evaluate the relative contributions to total ecosystem respiration (TER) of heterotrophic, above ground autotrophic and below ground autotrophic respiration over a succession of three agricultural crops (seed potato, winter wheat and sugar beet) cultivated on successive years at the same location and, secondly, to identify the driving variables of these contributions.Results showed that, during the observation periods, TER was dominated by autotrophic respiration (AR) (60-90%) and that AR was dominated by its above ground component (60-80%). HR was found to increase with temperature and to be independent of Gross Primary Production (GPP), whereas AR was driven by GPP and was mostly independent of temperature. The AR response to GPP was specific to the crop: not only AR intensity but also AR distribution between its above- (ARa) and below- (ARb) ground components were found to differ from one crop to another and, in the winter wheat, from one development stage to another. Generally, ARb contribution to AR was found larger when carbon allocation towards roots was more important.An uncertainty analysis was made and showed that the main sources of uncertainties on the estimates were the spatial variability for soil chamber measurements and uncertainties linked to the data gap filling method for eddy covariance measurements.     

AE—Automation and Emerging Technologies: On-line Fruit Grading according to their External Quality using Machine Vision

This paper presents apple grading into four classes according to European standards. Two varieties were tested: Golden Delicious and Jonagold. The image database included more than a 1000 images of fruits (528 Golden Delicious, 642 Jonagold) belonging to the three acceptable categories—Extra, I and II—and the reject (each class represents, respectively, about 60, 10 and 20% of the sample size).The image grading was achieved in six steps: image acquisition; ground colour classification; defect segmentation; calyx and stem recognition; defects characterisation and finally the fruit classification into quality classes.The proposed method for apple external quality grading showed correct classification rates of 78 and 72%, for Golden Delicious and Jonagold apples, respectively. Taking into account that the healthy fruit were far better graded and considering that this class was under represented in the sample compared with the fruit population, the results of the proposed method (an error rate which drops to 5 and 10%, respectively) are compatible with the requirements of European standards.     

Influence of purified dietary fibre on bacterial protein synthesis in the large intestine of pigs, as measured by the gas production technique

Microbial fermentation of non-digestible carbohydrates in the pig's large intestine induces a shift of N excretion from urea in urine to bacterial protein in faeces. Experiments were carried out to measure the mineral N incorporation by the pig intestinal microflora using 5 purified carbohydrates in a gas-test: starch (S), cellulose (C), inulin (I), pectin (P) and xylan (X). Fermentation kinetics was modelled. N source in the buffer solution was replaced by ¹⁵N labelled NH₄Cl. The bacterial N fixation was determined at mid-fermentation, measuring ¹⁵N incorporation into the solid phase of the buffer. The bacterial N fixation was higher (P < 0.001) with I and S (19.9 and 18.1 mg N/g incubated DM), compared to P, C and X (8.7, 5.9 and 5.5 respectively). Inulin and S were fermented also more rapidly, even if I (0.081 h^− 1) and C (0.074 h^− 1) showed lower half time fractional rate of degradation than S (0.153 h^− 1), P (0.133 h^− 1) and X (0.104 h^− 1). The insoluble dietary fibre content of the substrates was negatively correlated to bacterial N fixation (r = − 0.957, P = 0.011). The high crude protein content of P (32.5 mg g^− 1DM) might explain the lower impact of this substrate on bacterial N fixation, despite its rapid fermentation. Beside the proportion of insoluble fibre, the N content and the rate of fermentation seem to be the major factors influencing bacterial protein synthesis. Further studies including ingredients with variable content of indigestible protein and mean retention time in the pig's intestines are necessary.     

Assessing the potential of an algorithm based on mean climatic data to predict wheat yield

The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3–4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days.     

Droplet size spectra and drift effect of two phenmedipham formulations and four adjuvants mixtures

The effect of 4 adjuvants on two formulations of phenmedipham (EC and SC) applied with three types of hydraulic nozzles (hollow cone, flat fan and air induction) was evaluated using a wind tunnel to determine spray drift potential (DP). The volume median diameter (VMD) and the percentage by volume of droplets less than 100 μm diameter was determined using a Malvern particle size analyser. In a wind tunnel DP was measured between 2 and 6 m downwind of the nozzle on glass fibre collectors using a fluorescent tracer. The EC formulation produced a smaller VMD and larger DP than the SC formulation irrespective of any effect due to adjuvants. DP increased as the proportion of small droplets increased.     

Automatic grading of Bi-colored apples by multispectral machine vision

In this paper we present a novel application work for grading of apple fruits by machine vision. Following precise segmentation of defects by minimal confusion with stem/calyx areas on multispectral images, statistical, textural and geometric features are extracted from the segmented area. Using these features, statistical and syntactical classifiers are trained for two- and multi-category grading of the fruits. Results showed that feature selection provided improved performance by retaining only the important features, and statistical classifiers outperformed their syntactical counterparts. Compared to the state-of-the-art, our two-category grading solution achieved better recognition rates (93.5% overall accuracy). In this work we further provided a more realistic multi-category grading solution, where different classification architectures are evaluated. Our observations showed that the single-classifier architecture is computationally less demanding, while the cascaded one is more accurate.