Does shifting from conventional to zero tillage in combination with a cover crop offers opportunities for silage maize cultivation in Flanders?

Tillage is an important agricultural practice, influencing the physical, chemical and biological soil characteristics. In this paper the influence of various tillage systems combined with or without a cover crop under different nitrogen fertilization levels on silage maize yield and soil fertility was investigated. Based on a field trial in Bottelare (Belgium), during the period 2007–2015, it was concluded that for each tillage system higher nitrogen levels resulted in a higher yield. In addition, the highest yield was achieved for the conventional tillage system, the yield gain for mouldboard ploughing varied between 13% (2015) and 71% (2012) compared to zero tillage. In case reduced tillage was adopted, the yield loss compared to mouldboard ploughing varied between 6% (2013 and 2015) and 24% (2012). Furthermore, it seemed that the accumulated temperature during the growing season and rainfall around flowering were decisive in determining maize yield. Additionally, rainfall in the period 60 days post sowing was significantly negatively correlated with the yield from the zero tillage plots, whereas in case tillage was adopted no correlations with rainfall 60 days post sowing were detected. Concerning the soil organic carbon content and the amount of earthworms, no clear trends could be observed. Zero tillage resulted in high weed pressure and caused soil compaction. So, in this trial, under humid conditions, the less labor intensive zero tillage system did not result in competitive maize yields. In conclusion, reduced tillage methods offer opportunities for maize cultivation in Belgium. This method of farming resulted in a lower yield, however, the difference with mouldboard ploughing was not significant. Therefore, adopting a reduced tillage system can be seen as a valid alternative for ploughing as this tillage system ensures a sustainable environment.     

The use of <Emphasis Type="Italic">Vp1</Emphasis> in real time RT-PCR to select for pre-harvest sprouting tolerance in triticale

In spite of the availability of laboratory and field tests there is still a major problem to select pre-harvest sprouting (PHS) tolerant triticale varieties in a reliable, field-independent way. One approach to minimize the influence of environmental conditions and physio-morphological traits on PHS detection is using molecular genetic tools. The ‘viviparous’ Vp1 gene has been repeatedly described to play an important role in dormancy in wheat. A quantitative RT-PCR assay based on the expression of the Vp1 gene has been developed. Specific primers were designed for detecting Vp1 in both wheat and triticale. The expression levels of Vp1 were normalized using reference genes and relatively quantified with the comparative C_t-method. However, the first results indicate that the achieved Vp1 expression levels at 50 days post anthesis are not useful to select for PHS tolerance, both in wheat and triticale. This negative outcome so far is possibly due to the existence of several splicing events or to the late assaying moment in the kernel development, when Vp1 expression is found to be low.     

The importance of non‐penetrated papillae formation in the resistance response of triticale to powdery mildew (Blumeria graminis)

Triticale is the intergeneric hybrid between wheat and rye. With the expansion of the triticale growing area, powdery mildew has emerged and become a significant disease on this new host. Recent research demonstrated that this ‘new’ powdery mildew on triticale has emerged through a host range expansion of powdery mildew of wheat. Moreover, isolates sampled from triticale still infect their previous host, wheat, but isolates sampled from wheat hardly infect triticale. Race‐specific and adult‐plant resistance have been identified in triticale cultivars. The main objective of this study was to characterize the cellular basis of powdery mildew resistance in triticale. Commonalities with resistance responses in other cereals such as wheat, barley and oat are discussed. A detailed comparative histological study of various resistance responses during cross‐inoculation of either virulent or avirulent wheat and triticale isolates on both hosts was carried out. The present data provide evidence that for incompatible interactions, the formation of non‐penetrated papillae is the predominant resistance response, while the hypersensitive response (HR) acts as a second line of defence, to cut the fungus off from nutrients, if penetration resistance fails. It is not clear yet what causes the slower growth and reduced colony size of triticale isolates when inoculated on wheat. Possibly, post‐penetration resistance mechanisms, other than HR, are switched on during these (semi‐) compatible interactions. Molecular studies on gene expression and gene function of defence‐related genes might reveal further insights into the genetic basis of these resistance responses.     

Effect of humic substances on nutrient uptake by herbage and on production and nutritive value of herbage from sown grass pastures

The effect of humic substances on the nutrient uptake, herbage production and nutritive value of herbage from sown grass pastures was studied in six field experiments. Commercial humic substances were applied in combination with mineral fertilizer or slurry, either as a solution (HF liquid; 8·3 kg humic substances ha⁻¹) or incorporated into the mineral fertilizer (HF incorporated; 3·6 to 6·4 kg humic substances ha⁻¹). A series of cuts, ranging from two to five cuts, was taken during the growing season. The general response in herbage production to application of humic substances was an increase in herbage mass of dry matter (DM) at the first cut although this was only significant in two experiments for the HF incorporated treatment. Total herbage production of DM over the growing season, however, was similar for treatments with or without application of humic substances. The overall effect of HF incorporated and HF liquid on the herbage mass of DM at the first cut across the experiments was calculated using a meta-analysis technique and it was shown that there was a significant proportional increase of 0·14 ( P  <   0·05) with the HF incorporated treatment and a non-significant increase of 0·08 with the HF liquid treatment compared to the control treatment. The nutritive value of the herbage at the first cut was similar across all treatments. In general nitrogen, phosphorus and potassium uptake at the first grass cut was higher after application of humic substances but only in one experiment was this increase statistically significant.     

Marker-based screening of maize inbred lines using support vector machine regression

The phenomenon of heterosis is widely used in hybrid breeding programmes, despite the fact that no satisfactory molecular explanation is available. Estimators of quantitative genetic components like GCA and SCA values are tools used by the plant breeder to identify superior parental individuals and to search for high heterosis combinations. Obtaining these estimators usually requires the creation of new parental combinations and testing their offspring in multi-environment field trials. In this study we explore the use of ɛ-insensitive Support Vector Machine Regression (ɛ-SVR) for the prediction of GCA and SCA values from the molecular marker scores of parental inbred lines as an alternative to these field trials. Prediction accuracies are obtained by means of cross-validation on a grain maize data set from the private breeding company RAGT R2n. Results indicate that the proposed method allows the routine screening of new inbred lines despite the fact that predicting the SCA value of an untested hybrid remains problematic with the available molecular marker information and standard kernel functions. The genotypical performance of a testcross hybrid, originating from a cross between an untested inbred line and a well-known complementary tester, can be predicted with moderate to high accuracy while this cannot be said for a cross between two untested inbred lines.     

Vp1 expression profiles during kernel development in six genotypes of wheat, triticale and rye

During the last few decades, the physiological and genetic background of dormancy, and correlated pre-harvest sprouting (PHS) have been intensively investigated. Special attention has often been paid to genetic factors that may explain and predict PHS susceptible behaviour. A major candidate is the Vp1 gene which is involved in embryo development and maturation as well as in dormancy establishment. In this study, Vp1 gene expression during kernel development was studied in wheat, triticale and rye as a potential biomarker for selecting PHS tolerant varieties in cereal breeding programs. Plants of known PHS tolerant and PHS susceptible varieties were grown under controlled conditions from flowering until harvest ripeness. During that period, kernels were regularly harvested for RNA extraction and cDNA synthesis. Calibrated and normalized relative Vp1 expression levels were obtained in an RT-qPCR assay. During kernel development, Vp1 expression levels generally showed a typical peak during the soft dough stage, after which they decreased and remained low until harvest maturity. Differences in Vp1 expression levels could be observed between the PHS susceptible and PHS tolerant varieties of wheat, with the PHS tolerant variety showing higher levels of relative Vp1 expression compared to the PHS susceptible variety. In triticale, however, this difference was only seen once and could not be confirmed in further experiments. It seems that the Vp1 gene in triticale behaves in a similar way as in rye, in which no specific trends could be observed.     

Multi-sensors data fusion approach for site-specific seeding of consumption and seed potato production

Precision Agriculture - This study evaluated the agronomic and economic prospects of Site-Specific Seeding (SSS) for consumption and seed potato production based on Management Zone (MZ) maps...     

Ordinal regression models for predicting deoxynivalenol in winter wheat

Deoxynivalenol (DON) is one of the most prevalent toxins in Fusarium‐infected wheat samples. Accurate forecasting systems that predict the presence of DON are useful to underpin decision making on the application of fungicides, to identify fields under risk, and to help minimize the risk of food and feed contamination with DON. To this end, existing forecasting systems often adopt statistical regression models, in which attempts are made to predict DON values as a continuous variable. In contrast, this paper advocates the use of ordinal regression models for the prediction of DON values, by defining thresholds for converting continuous DON values into a fixed number of well‐chosen risk classes. Objective criteria for selecting these thresholds in a meaningful way are proposed. The resulting approach was evaluated on a sizeable field experiment in Belgium, for which measurements of DON values and various types of predictor variables were collected at 18 locations during 2002–2011. The results demonstrate that modelling and evaluating DON values on an ordinal scale leads to a more accurate and more easily interpreted predictive performance. Compared to traditional regression models, an improvement could be observed for support vector ordinal regression models and proportional odds models.     

Identifying drivers of spatio‐temporal dynamics in barley yellow dwarf virus epidemiology as a critical factor in disease control

Barley yellow dwarf virus (BYDV) is one of the most important viral diseases of small grains worldwide. An understanding of its epidemiology is crucial to control this disease in a sustainable way. The virus moves through the agricultural landscape via cereal aphids as vectors. Understanding movement of these aphids in space and time is of key importance and in doing so, the spatial and temporal variables that influence BYDV epidemiology can be identified. The presence of summer hosts, crop rotation, crop diversity, agricultural practices and climate variables are crucial. Through digitalization, spatial (e.g. land‐use) and temporal (e.g. weather) information is becoming more readily available. Including this information into a prediction model could improve decision support systems that will rationalize the decision‐making process towards a more integrated control of the disease. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Potentials and Limitations of Existing Forecasting Models for <Emphasis Type="Italic">Alternaria</Emphasis> on Potatoes: Challenges for Model Improvement

Alternaria species, including A. solani and A. alternata, are a serious threat to potato cultivation and cause necrotic leaf spots, leading to premature defoliation and yield losses. To reduce the impact of the disease, a timely prediction of a disease outbreak is important. Worldwide, modelling attempts have been made to predict the occurrence of Alternaria in order to take adequate measures. In the present paper, we made an effort to classify the existing prediction models and subdivided them into three categories: plant-based, pathogen-based and plant-pathogen-based models. Plant-based models predict the susceptibility of the host crop and presume that Alternaria inoculum is abundantly present and not the restrictive factor, whereas pathogen-based models consider one or more stages of the Alternaria life cycle and suppose that the host crop is always susceptible. The plant-pathogen-based models try to take into account the complete plant-pathogen-environment relationship. In this paper, a critical review of the described models for Alternaria leaf spot is presented. To illustrate the discrepancy between the predicted and the observed dates of the first Alternaria symptoms or the discrepancy between the suggested first treatment and necessity to treat Alternaria, the existing models were subjected to the Belgian weather conditions. It turns out that these models are not applicable in Belgium or similar regions. This can be partially attributed to the fact that most of the currently available models are too simplistic (only plant- or pathogen-based) for regions where the disease pressure highly fluctuates between growing seasons and between locations within one season. Finally, perspectives for model improvement are given taking into account both plant, pathogen and environment.