Dividing fields into a few relatively homogeneous management zones (MZs) is a practical and cost-effective approach to precision agriculture. There are three basic approaches to MZ delineation using soil and/or landscape properties, yield information, and both sources of information. The objective of this study is to propose an integrated approach to delineating site-specific MZ using relative elevation, organic matter, slope, electrical conductivity, yield spatial trend map, and yield temporal stability map (ROSE-YSTTS) and evaluate it against two other approaches using only soil and landscape information (ROSE) or clustering multiple year yield maps (CMYYM). The study was carried out on two no-till corn-soybean rotation fields in eastern Illinois, USA. Two years of nitrogen (N) rate experiments were conducted in Field B to evaluate the delineated MZs for site-specific N management. It was found that in general the ROSE approach was least effective in accounting for crop yield variability (8.0%–9.8%), while the CMYYM approach was least effective in accounting for soil and landscape (8.9%–38.1%), and soil nutrient and pH variability (9.4%–14.5%). The integrated ROSE-YSTTS approach was reasonably effective in accounting for the three sources of variability (38.6%–48.9%, 16.1%–17.3% and 13.2%–18.7% for soil and landscape, nutrient and pH, and yield variability, respectively), being either the best or second best approach. It was also found that the ROSE-YSTTS approach was effective in defining zones with high, medium and low economically optimum N rates. It is concluded that the integrated ROSE-YSTTS approach combining soil, landscape and yield spatial-temporal variability information can overcome the weaknesses of approaches using only soil, landscape or yield information, and is more robust for MZ delineation. It also has the potential for site-specific N management for improved economic returns. More studies are needed to further evaluate their appropriateness for precision N and crop management.

Precision crop management for optimizing yield and quality is important for developing a consistent product for different end uses of grain. This study was conducted to evaluate the potential impact of variable‐rate N (VRN) application, hybrid selection, and hybrid‐specific N management on corn ( Zea mays L.) yield, protein content, and test weight. On‐farm experiments were conducted during three site‐years in eastern Illinois using a split‐plot design, with the main plots consisting of five N rates and the subplots two corn hybrids (Pioneer 33G26 and 33J24). Nitrogen response curves of corn yield and quality were fitted at 19 and 16 within‐field locations in Fields 1 and 2, respectively, and the potential impacts of different N management strategies were evaluated. Results indicated that within‐field economically optimum N rates (EONR) ranged from 82 to 336 kg N ha −1 , while N rates that would maximize grain quality ranged from 0 to 336 kg N ha −1 Compared with a uniform‐rate N (URN) application of 168 kg N ha −1 , the VRN application at EONR would increase corn yield for hybrid 33J24 while having an inconsistent impact on yield of 33G26, without significantly improving grain quality of either hybrid. Hybrid 33J24 would have higher yield, quality, and economic returns than 33G26 under either URN or VRN application. Hybrid‐specific N applications could have either negative or positive impacts on corn yield and protein content, without significantly affecting test weight. These results suggest that selecting the right hybrid(s) was more important and practical than the evaluated precision N management practices for optimizing both corn yield and grain quality during the study site‐years.

Soil, landscape and hybrid factors are known to influence yield and quality of corn ( Zea mays L.). This study employed artificial neural network (ANN) analysis to evaluate the relative importance of selected soil, landscape and seed hybrid factors on yield and grain quality in two Illinois, USA fields. About 7 to 13 important factors were identified that could explain from 61% to 99% of the observed yield or quality variability in the study site-years. Hybrid was found to be the most important factor overall for quality in both fields, and for yield as well in Field 1. The relative importance of soil and landscape factors for corn yield and quality and their relationships differed by hybrid and field. Cation exchange capacity (CEC) and relative elevation were consistently identified as among the top four most important soil and landscape factors for both corn yield and quality in both fields in 2000. Aspect and Zn were among the top five most important factors in Fields 1 and 2, respectively. Compound topographic index (CTI), profile curvature and tangential curvature were, in general, not important in the study site-years. The response curves generated by the ANN models were more informative than simple correlation coefficients or coefficients in multiple regression equations. We conclude that hybrid was more important than soil and landscape factors for consideration in precision crop management, especially when grain quality was a management objective.

Determining MZ (management zone)‐specific optimal N rate is a challenge in precision crop management. The objective of this study was to evaluate the potential of applying a crop growth model to simulate corn (Zea mays L.) yield at various N levels in different MZs and estimate optimal N rates based on long‐term weather conditions. Three years of corn yield data were used to calibrate a modified version of the CERES‐Maize (Version 3.5) model for a commercial field previously divided into four MZs in eastern Illinois. The model performance in simulating corn yield for two hybrids (33G26 and 33J24) at five N levels in two independent years was evaluated. Economically optimum N rates (EONRs) were estimated based on 15 yr of simulation (1989–2003). The model explained approximately 59 and 93% of yield variability during calibration and validation, respectively. The model performed well at non‐zero N rates, with most of the simulation errors being <10%. Model‐estimated EONR varied from 70 to 250 kg ha−1. Economic analyses indicated that applying N fertilizer at year‐, hybrid‐, and MZ‐specific EONR had the potential to increase net return by an average of US$49 (33G26) or US$52 (33J24) ha−1 over a URN (uniform rate N) application at 170 kg ha−1. Applying average hybrid‐ and MZ‐specific EONRs across years did not consistently improve economic returns over URN application; however, applying the hybrid‐ and MZ‐specific N rates that maximized long‐term net returns would improve economic return by an average of US$22 (33G26) and US$14 (33J24) ha−1

A better awareness of soil and crop condition variability within fields brought the notion, in the early 1980s that variable management within fields by zones rather than whole fields would increase profitability by doing the right thing at the right place in the right way. At the same time, the microcomputer became available and made possible the acquisition, processing, and use of spatial field data as well as the development of a new kind of farm machinery with computerized controllers and sensors. Precision agriculture (PA) has been considered for most common cropping systems and some specialty crops, worldwide. It is particularly well adapted to high value crops such as many horticultural crops. PA is still in infancy and its adoption varies greatly but precision agriculture is the agricultural system of the future. It offers a variety of potential benefits in profitability, productivity, sustainability, crop quality, food safety, environmental protection, on-farm quality of life, and rural economic development.

9-hydroxy-dihydrofuro-2,3b-tetrahydropyran is synthesised as a model substance for azadirachtin. The key step utilizes cyclisation of hydroxy-dialdehyde precursors, followed by acetylation and pyrolysis.

Twenty-two diversely substituted butadiynes have been tested for their insect antifeeding activity against Mythimna unipuncta, Spodoptera littoralis and Leptinotarsa decemlineata. The results in form of PA50 (50% feeding of reference test) were submitted to Hansch linear regression analysis. Essentially steric but also electronic and hydrophobic factors prove to be statistically significant to explain the variation of activity.

Eleven furocoumarins from Angelica silvestris and Heracleum sphondylium were tested for their antifeedant activity gainst two insect larvae: Mythimna unipuncta and the Colorado beetle Leptinotarsa decemlineata. Angular furocoumarins show a smaller effect that the corresponding linear homologues. The following order of activity is observed for substituents: 4-Methoxybenzofuran, a synthetic analogue shows also medium activity. But the most active component is a sesquiterpene: the known bisabolangelone.

Chemical factors have an important role in the host plant/insect relationship. Yet insects are living in a complex environment consisting not only of host plants, but also of many non‐host plants. The latter also release chemical signals that may be perceived by insects.We show here how a non‐host plant (chestnut) affects the sugar beet moth's reproduction. The chestnut compounds inhibit mating and egg‐laying behaviour and mask the chemical stimulating effect of the beet on oogenesis and oviposition. In this way they act in laboratory conditions by reducing the reproductive potential of an oligophagous insect, and in field conditions they lower population density.These results reveal the possible role of non‐host plant compounds, and their identification will open new prospects in pest management by manipulating the behaviour of insects.RÉSUMÉACTION D'UN EXTRAIT DE PLANTE NON HȮTE SUR LA REPRODUCTION D'UN INSECTE PHYTOPHAGE OLIGOPHAGE: LA TEIGNE DE LA BETTERAVE SCROBIPALPA OCELLATELLA BOYD. (LEPIDOPTERA GELECHIIDAE)Les signaux chimiques émis par la betterave attirent la femelle pondeuse pour le choix d'un support de ponte, stimulent l'ovogènese, stimulent les accouplements et la ponte.L'extrait aqueux de feuilles de châtaignier, plante non hôte, inhibe les accouplements et la ponte; pulvérisé sur une betterave, il masque l'action stimulante de la plante‐hôte sur l'ovogénèse et la ponte. Pulvérisé sur des parcelles de betterave dans la nature, l'extrait de châtaignier entraîne une diminution de près de la moitié de la densité de population.Dans les communautés végétales naturelles de nombreuses espèces de plantes sont intimement mélangées. Les signaux chimiques émis par les plantes non hôtes peuvent masquer la plante‐hôte qui n'est pas perçue et n'est pas découverte. Ces signaux chimiques peuvent aussi diminuer le potentiel de reproduction et modifier la dynamique de population de l'insecte phytophage. L'étude des substances présentes dans les plantes non hôtes doit ouvrir de nouvelles perspectives dans la protection des plantes cultivées.