Soybean is often intercropped with maize, sugarcane, and sorghum.  Because of the shade coming from the latter, the soybean stem lodging is often a very serious problem in intercropping systems.  The aim of this study is to characterize the possible mechanisms in the stem of shade-induced promotion of seedling soybean lodging in intercropping systems at the proteome level.  We found that the soybean stem became slender and prone to lodging when it was planted with maize in an intercropping system.  The inhibition of lignin biosynthesis and lack of photosynthate (soluble sugar) for the biosynthesis of the cell wall led to the lower internode breaking strength.  A total of 317 proteins were found to be affected in the soybean stem in response to shade.  Under the shade stress, the down-expression of key enzymes involving the phenylpropanoid metabolic pathway inhibited lignin biosynthesis.  The up-regulation of expansin and XTHs protein expression relaxed the cell wall and promoted the elongation of internodes.  Although the expression of the enzymes involving sucrose synthesis increased in the soybean stem, the lack of a carbon source prevented rapid stem growth.  This metabolic deficit is the principal cause of the lower cellulose content in the stem of intercropped soybean, which leads to weakened stems and a propensity for lodging.

Timely crop acreage and distribution information are the basic data which drive many agriculture related applications.  For identifying crop types based on remote sensing, methods using only a single image type have significant limitations.  Current research that integrates fine and coarser spatial resolution images, using techniques such as unmixing methods, regression models, and others, usually results in coarse resolution abundance without sufficient detail within pixels, and limited attention has been paid to the spatial relationship between the pixels from these two kinds of images.  Here we propose a new solution to identify winter wheat by integrating spectral and temporal information derived from multi-resolution remote sensing data and determine the spatial distribution of sub-pixels within the coarse resolution pixels.  Firstly, the membership of pixels which belong to winter wheat is calculated using a 25-m resolution resampled Landsat Thematic Mapper (TM) image based on the Bayesian equation.  Then, the winter wheat abundance (acreage fraction in a pixel) is assessed by using a multiple regression model based on the unique temporal change features from moderate resolution imaging spectroradiometer (MODIS) time series data.  Finally, winter wheat is identified by the proposed Abundance-Membership (AM) model based on the spatial relationship between the two types of pixels.  Specifically, winter wheat is identified by comparing the spatially corresponding 10×10 membership pixels of each abundance pixel.  In other words, this method takes advantage of the relative size of membership in a local space, rather than the absolute size in the entire study area.  This method is tested in the major agricultural area of Yiluo Basin, China, and the results show that acreage accuracy (Aa) is 93.01% and sampling accuracy (As) is 91.40%.  Confusion matrix shows that overall accuracy (OA) is 91.4% and the kappa coefficient (Kappa) is 0.755.  These values are significantly improved compared to the traditional Maximum Likelihood classification (MLC) and Random Forest classification (RFC) which rely on spectral features.  The results demonstrate that the identification accuracy can be improved by integrating spectral and temporal information.  Since the identification of winter wheat is performed in the space corresponding to each MODIS pixel, the influence of differences of environmental conditions is greatly reduced.  This advantage allows the proposed method to be effectively applied in other places.

Lodging is the most important constraint for soybean growth at seedling stage in maize-soybean relay strip intercropping system.  In the field experiments, three soybean cultivars Nandou 032-4 (shade susceptible cultivar; B1), Jiuyuehuang (moderately shade tolerant cultivar; B2), and Nandou 12 (shade tolerant cultivar; B3) were used to evaluate the relationship between stem stress and lignin metabolism in the stem of soybean.  Results showed that the intercropped soybean was in variable light condition throughout the day time and co-growth stage with maize.  The xylem area and cross section ratio played a main role to form the stem stress.  The B3 both in intercropping and monocropping expressed a high stem stress with higher xylem area, lignin content, and activity of enzymes (phenylalanine ammonia-lyase (PAL), 4-coumarate: CoA ligase (4CL), cinnamyl alcohol dehydrogenase (CAD), and peroxidase (POD)) than those of B1 and B2.  Among the soybean cultivars and planting pattern, lignin content was positively correlated with stem stress.  However, a negative correlation was found between lignin content and actual rate of lodging.  In conclusion, the shade tolerant soybean cultivar had larger xylem area, higher lignin content and activities of CAD, 4CL, PAL, and POD than other soybean cultivars in intercropping.  The lodging in maize-soybean intercropping can be minimized by planting shade tolerant and lodging resistant cultivar of soybean.  The lignin content in stem could be a useful indicator for the evaluation of lodging resistance of soybean in intercropping and activities of enzymes were the key factors that influence the lignin biosynthesis.

Intercropping is an important agronomic practice.  However, assessment of intercropping systems using field experiments is often limited by time and cost.  In this study, the suitability of using the DeNitrification DeComposition (DNDC) model to simulate intercropping of maize (Zea mays L.) and soybean (Glycine max L.) and its aftereffect on the succeeding wheat (Triticum aestivum L.) crop was tested in the North China Plain.  First, the model was calibrated and corroborated to simulate crop yield and nitrogen (N) uptake based on a field experiment with a typical double cropping system.  With a wheat crop in winter, the experiment included five treatments in summer: maize monoculture, soybean monoculture, intercropping of maize and soybean with no N topdressing to maize (N0), intercropping of maize and soybean with 75 kg N ha^–1 topdressing to maize (N75), and intercropping of maize and soybean with 180 kg N ha^–1 topdressing to maize (N180).  All treatments had 45 kg N ha^–1 as basal fertilizer.  After calibration and corroboration, DNDC was used to simulate long-term (1955 to 2012) treatment effects on yield.  Results showed that DNDC could stringently capture the yield and N uptake of the intercropping system under all N management scenarios, though it tended to underestimate wheat yield and N uptake under N0 and N75.  Long-term simulation results showed that N75 led to the highest maize and soybean yields per unit planting area among all treatments, increasing maize yield by 59% and soybean yield by 24%, resulting in a land utilization rate 42% higher than monoculture.  The results suggest a high potential to promote soybean production by intercropping soybean with maize in the North China Plain, which will help to meet the large national demand for soybean.

To clarify how shade stress affects lignin biosynthesis in soybean stem, two varieties, Nandou 12 (shade tolerant) and Nan 032-4 (shade susceptible) grew under normal light and shade conditions (the photosynthetically active radiation and the ratio of red:far-red were lower than normal light condition).  Lignin accumulation, transcripts of genes involved in lignin biosynthesis, and intermediates content of lignin biosynthesis were analyzed.  Both soybean varieties suffered shade stress had increased plant heights and internode lengths, and reduced stem diameters and lignin accumulation in stems.  The expression levels of lignin-related genes were significantly influenced by shade stress, with interactions between the light environment and variety.  The gene of 3-hydroxylase (C3H), cinnamoyl-CoA reductase (CCR), caffeoyl-CoA O-methyltransferase (CCoAOMT), and peroxidase (POD) attributed to lignin biosynthesis under shade stress, and the down-regulation of these genes resulted in lower caffeic, sinapic, and ferulic acid levels, which caused a further decrease in lignin biosynthesis.  Under shade stress, the shade tolerant soybean variety (Nandou 12) showed stiffer stems, higher lignin content, and greater gene expression level and higher metabolite contents than shade susceptible one.  So these characteristics could be used for screening the shade-tolerant soybean for intercropping.