Effectiveness of solar blinkers as a means of crop protection from wild boar damage

The population density of wild boar (Sus scrofa) in Northern Switzerland has increased dramatically during the last three decades and the species has become a major threat to agriculture, causing severe damage to crops and grassland. Vulnerable fields have to be protected from wild boar incursion, which is in most cases achieved by using electric fences. Alternatively, deterrents basing on optical, acoustical or gustative effect are available. The effectiveness of most of these systems has not previously been scientifically tested in the field. In our study we investigated the effectiveness of solar blinkers at baited luring sites. We conducted field experiments at 4 different sites with free-ranging wild boars from January 2007 to January 2008. Data from 504 inspections of the luring sites indicate that solar blinkers reduced the probability of wild boar visits at the luring sites by 8.1% compared to the control sites. We therefore evaluate deterrence effect of solar blinkers to be insufficient for effective crop protection. Probability of wild boar visits at the luring sites changed throughout the study period, showing seasonal variation of the extent of wild boar activity in the fields.     

Effects and fate of biochar from rice residues in rice-based systems

Although crop residues constitute an enormous resource, actual residue management practices in rice-based systems have various negative side effects and contribute to global warming. The concept of a combined bioenergy/biochar system could tackle these problems in a new way. Rice residues would be used for energy production, thereby reducing field burning and the use of fossil fuels, and the biochar by-product could help to improve soils, avoid methane emissions, and sequester carbon in soils. To examine some of these promises, we conducted field experiments from 2005 to 2008 in three different rice production systems. Objectives were to study the effect of biochar from rice husks on soil characteristics, assess the stability of carbonized rice residues in these different systems, and evaluate the agronomic effect of biochar applications. The results showed that application of untreated and carbonized rice husks (RH and CRH) increased total organic carbon, total soil N, the C/N ratio, and available P and K. Not significant or small effects were observed for soil reaction, exchangeable Ca, Mg, Na, and the CEC. On a fertile soil, the high C/N ratio of CRH seemed to have limited N availability, thereby slightly reducing grain yields in the first three seasons after application. On a poor soil, where the crop also suffered from water stress, soil chemical and physical improvements increased yields by 16-35%. Together with a parallel study including methane and CO₂ emission measurements at one site, the results strongly suggest that CRH is very stable in various rice soils and systems, possibly for thousands of years. However, the study also showed that CRH was very mobile in some soils. Especially in poor sandy soil, about half of the applied carbon seemed to have moved below 0.30 m in the soil profile within 4 years after application. We concluded that biochar from rice residues can be beneficial in rice-based systems but that actual effects on soil fertility, grain yield, and soil organic carbon will depend on site-specific conditions. Long-term studies on biochar in field trials seem essential to better understand biochar effects and to investigate its behavior in soils.     

Characterizing multiple linkages between individual diseases,crop health syndromes,germplasm deployment,and rice production situations in India

Five groups of crop health syndromes, four production situations, and three patterns of germplasm deployment were identified and characterized from a data set consisting of information from 129 Indian districts, which were surveyed in 2005 as part of the Production-Oriented Surveys conducted by the Directorate of Rice Research of the Indian Council of Agricultural Research. ANOVAs and MANOVAs indicated that these groupings from hierarchical cluster analyses correspond to clearly different levels of disease and animal pest injuries (crop health syndromes): of crop rotation, crop management, agricultural resources, and inputs (production situations); and of deployment of traditional, high yielding, or hybrid plant material (patterns of germplasm deployment). Correspondence analysis and discriminant analyses further indicated that crop health syndromes, and their change, are strongly associated with production situations, and patterns of germplasm deployment. A few specific hypotheses were tested, indicating that false smut is statistically associated with the involvement of hybrid rice in patterns of germplasm deployment. This highlights the need for research on the biology and the epidemiology of this disease in order to develop suitable management tools. Importantly, this work shows that national surveys, such as the Production-Oriented Surveys conducted by the Directorate of Rice Research, generate extremely valuable information to guide research and development through the characterization of production environments, contexts, and crop health responses, in times of unprecedented agricultural change. This work concurs with earlier results obtained at the field level, and thus opens important methodological questions regarding the up- and down-scaling of information between different scales (e.g., field, district). We propose that our ability to predict emerging diseases and crop health syndromes in the face of global and climate change will necessarily entail our ability to link different scales, where a range of different processes, biological and socio-economic, take place.     

南宁市农作物套种栽培技术的推广与应用

为贯彻实施自治区农业厅＂三个千万亩增粮增收行动计划＂,南宁市以农业优势产业为重点,全面推广应用农作物间套种栽培技术。文章主要介绍南宁市推广农作物套种技术的基本做法和成效,并针对间套种技术推广工作中存在的问题,提出今后开展间套种技术推广的5点建议。     

秸秆利用现状及其生物炭化前景探析——以辽宁省彰武县为例

随着作物产量水平的提高和农民生活质量的改善,我国秸秆等废弃物资源相对过剩现象变得更为普遍。以辽宁省彰武县为例,在辨别该地区主要农业产品生产情况的基础上,分析了其秸秆等主要农业副产品的综合利用现状,并探讨了秸秆等农业副产品进行生物炭化的经济效益、社会效益和生态效益。通过秸秆炭化前景的分析,可以看出,为了实现逐年降低秸秆焚烧比例、提高秸秆综合利用率、最终实现零焚烧的目的,开展秸秆等农业副产品的生物炭化利用是一条可行的路径。     

Neural network modeling of greenhouse tomato yield, growth and water use from automated crop monitoring data

The recent development of tools to automatically monitor important crop attributes in situ such as yield, growth and water use offers an opportunity to relate real-time crop status to current environmental conditions. In this study, continuous minute-by-minute measurements of crop yield, growth and water use averaged over weekly, daily, or hourly intervals throughout the growing season were used to determine crop response to changes in the greenhouse environment. The data were obtained from crop monitoring stations established in both commercial and research greenhouses. Crop yield measurements obtained from the monitoring system were generally in very close agreement with yields recorded over a much larger area in the commercial greenhouse. Yield was more closely related (R² = 0.65) to radiation from the previous week than to radiation in the current week (R² = 0.56). In addition, a neural network (NN) model of yield which included radiation as an input was better at predicting yield in the following week (R² = 0.70) than yield in the current week (R² = 0.57). These results indicate a lag effect of radiation on yield. Similarly, yield was more positively related to growth from the previous week (R² = 0.32) than to growth from the current week (R² = 0.17). Neural network models of daily growth at both sites (R² = 0.74, 0.69) included day of the year, temperature and CO₂ as inputs. A negative relationship between day of the year and daily growth indicates a decline in crop vigor through the measurement period. Neural network models of daily crop water use for the two sites were stronger (R² = 0.91, 0.85) than those for growth, highlighting the difference in physiological complexity between the two. A model of canopy water status as affected by environmental conditions was generated using hourly measures of tomato canopy mass change. Although the rate of canopy mass gain through the day was often constant, there were days when the plant experienced periods of reduced mass gain mid-day. On those days, the amount of deviation from a constant rate was positively related to radiation, day temperature and water use, suggesting periods of water stress. With subsequent recovery of mass gain rates late afternoon, these deviations did not affect canopy growth for the day. Overall, automated monitoring provides new information on the crop which may readily be incorporated into models of crop performance.     

Evaluating high resolution SPOT 5 satellite imagery for crop identification

High resolution satellite imagery offers new opportunities for crop monitoring and assessment. A SPOT 5 image acquired in May 2006 with four spectral bands (green, red, near-infrared, and short-wave infrared) and 10-m pixel size covering intensively cropped areas in south Texas was evaluated for crop identification. Two images with pixel sizes of 20 m and 30 m were also generated from the original image to simulate coarser resolution satellite imagery. Two subset images covering a variety of crops with different growth stages were extracted from the satellite image and five supervised classification techniques, including minimum distance, Mahalanobis distance, maximum likelihood, spectral angle mapper (SAM), and support vector machine (SVM), were applied to the 10-m subset images and the two coarser resolution images to identify crop types. The effects of the short-wave infrared band and pixel size on classification results were also examined. Kappa analysis showed that maximum likelihood and SVM performed better than the other three classifiers, though there were no statistical differences between the two best classifiers. Accuracy assessment showed that the 10-m, four-band images based on maximum likelihood resulted in the best overall accuracy values of 91% and 87% for the two respective sites. The inclusion of the short-wave infrared band statistically significantly increased the overall accuracy from 82% to 91% for site 1 and from 75% to 87% for site 2. The increase in pixel size from 10 m to 20 m or 30 m did not significantly affect the classification accuracy for crop identification. These results indicate that SPOT 5 multispectral imagery in conjunction with maximum likelihood and SVM classification techniques can be used for identifying crop types and estimating crop areas.     

信息不对称下烟草农业发展研究——以广西百色市为例

采用抽样和问卷调查,对广西百色市的烟草农业发展进行研究,结果表明,百色市烟草农业发展中存在宣传引导和培训力度不够,轮作机制不合理,烟叶烘烤技术差,专业化服务水平低,生产资料及用工的成本不断增加,信息化管理水平不高以及生产事故多的问题。对比,需要强化宣传及培训,加大技术支持,科学发展烟农合作社,提升服务质量,减工降本,提升信息化管理水平,降低制度运行成本,加强安全生产指导等,以保障在信息不对称环境下,促进广西乃至全国烟草农业的健康有序发展。     

春玉米化学氮肥投入阈值研究

通过田间试验,研究不同氮素水平(0、150、200、250、300、400 kg/hm~2)对春玉米植株地上部分吸氮量、农田矿质氮平衡和玉米产量的影响。结果表明,土壤中矿质氮随土层深度的增加逐渐降低,硝态氮在20~40 cm和100~120cm各有1个积累峰值。在0~40 cm土层深度内,N0和N150处理铵态氮含量低于其他处理。当施氮量264.16 kg/hm~2时,玉米植株吸氮量与施氮量呈正相关;当施氮量≥264.16 kg/hm~2时,施氮量对玉米植株吸氮量增加不显著(p0.01)。0~120cm土壤氮素表观损失量和施氮量呈正相关,当施氮量221.36 kg/hm~2时,氮肥供应不足。本试验条件下,化学氮肥施用阈值为221.36~264.16 kg/hm~2,最高产量施氮量为252.93 kg/hm~2。     

淮北地区小麦超高产群体生长特性分析

为了解安徽省淮北地区超高产小麦群体生长指标与产量之间的关系,于2011-2014年度,以当地种植面积较大、具有超高产潜力的小麦品种济麦22和皖麦52为试验材料,研究了播期和播种密度对小麦群体生长指标和产量的影响。结果发现,年度间比较,2013-2014年度的小麦产量较高;播期为10月3日时,两个小麦品种的产量随密度的增加呈先增加后降低趋势,均以密度为210×104株·hm-2处理产量最高;播期为10月15日时,两个小麦品种的产量随密度增加而增加,均以密度为330×104株·hm-2处理产量最高。早播(10月3日)处理的小麦,叶面积持续时间较长;播期相同时,小麦的叶面积持续时间随密度增加而增加,叶面积指数随密度增加而减少,净同化率随密度增加而增加。小麦群体生长率的增加,主要来源于叶面积指数的增加。相关性分析表明,小麦籽粒产量与其叶面积持续时间和群体生长率的相关性极显著,与净同化率呈显著负相关。本试验条件下,两个小麦品种均以10月3日播种、密度为210×104株·hm-2处理的产量最高。