Application of Trichoderma harzianum in the control of basal stem rot of oil palms

The palm, Elaeis guineensis, has its origins in Africa but is planted on a commercial basis in several countries Statistics for 2002 showed that in the lead for land mass under oil palm cultivation is Indonesia, at 3,769,000 ha, followed by Malaysia at 3,376,000 ha; however, the world‘s leading     

油棕茎基腐病研究进展

由灵芝菌引起的茎基腐病是油棕生产上的最主要病害之一,在亚洲、非洲、中南美洲和大洋洲等地均有报道.给东南亚的油棕产业带来了巨大损失.综述了油棕茎基腐病的分布与危害、病害症状学、病原物与传播途径、防控技术等方面的研究进展.     

Multi-temporal analysis of terrestrial laser scanning data to detect basal stem rot in oil palm trees

Terrestrial laser scanning technology is an advanced active remote sensing ranging method that is well suited for yielding high-resolution scans of the morphology of a tree, which is an indicator of the health of the plant. The Ganoderma boninense fungus causes basal stem rot (BSR), which threatens the oil palm industry in Malaysia. To date, the current practice of inspection in a plantation is conducted every 6 months. Monitoring the progress with a closer gap is required to comprehend if any changes can be seen earlier than 6 months. Therefore, the objectives of this study were to identify the most suitable parameters of the oil palm trees to detect the BSR disease based on temporal laser scanning data and to identify suitable time frames for monitoring the progress of the symptoms of the disease. Terrestrial laser scanning data was used to analyse changes in the crown and frond metrics of oil palm trees with two different scan durations i.e., 2- and 4-months after the first scan. This spatio-temporal data is important in the precision agriculture field for better oil palm management, to understand the disease development for long-term solutions and also to provide a fast response so that appropriate treatment can be given to the palm as early as possible. Statistical analyses, i.e., the Kruskal–Wallis test with α?=?0.05 and the Wilcoxon post-hoc test, were conducted to determine significant differences in the parameters at different points in time. The results show that crown strata number 17 (850 cm from the top) and the crown area were the most suitable parameters to be used. Furthermore, the oil palm trees with BSR can be detected by comparing the 4-month scan or the second 2-month scan. The results have shown that the effect of Ganoderma boninense infection can be differentiated at the later stage. In conclusion, the changes can be measured at 4-months after the first inspection, thus helping to preventing crop losses.

     

Comparison of QuickBird Satellite Imagery and Airborne Imagery for Mapping Grain Sorghum Yield Patterns

Timely and accurate information on crop conditions obtained during the growing season is of vital importance for crop management. High spatial resolution satellite imagery has the potential for mapping crop growth variability and identifying problem areas within fields. The objectives of this study were to use QuickBird satellite imagery for mapping plant growth and yield patterns within grain sorghum fields as compared with airborne multispectral image data. A QuickBird 2.8-m four-band image covering a cropping area in south Texas, USA was acquired in the 2003 growing season. Airborne three-band imagery with submeter resolution was also collected from two grain sorghum fields within the satellite scene. Yield monitor data collected from the two fields were resampled to match the resolutions of the airborne imagery and the satellite imagery. The airborne imagery was related to yield at original submeter, 2.8 and 8.4 m resolutions and the QuickBird imagery was related to yield at 2.8 and 8.4 m resolutions. The extracted QuickBird images for the two fields were then classified into multiple zones using unsupervised classification and mean yields among the zones were compared. Results showed that grain yield was significantly related to both types of image data and that the QuickBird imagery had similar correlations with grain yield as compared with the airborne imagery at the 2.8 and 8.4 m resolutions. Moreover, the unsupervised classification maps effectively differentiated grain production levels among the zones. These results indicate that high spatial resolution satellite imagery can be a useful data source for determining plant growth and yield patterns for within-field crop management.     

Accuracy comparison of cabbage coverage estimated from remotely sensed imagery using an unmixing method

In this study, accuracy comparisons of the cabbage coverage estimated from AVNIR-2 and QuickBird imagery using an unmixing method were carried out to increase the amount of remote sensing data obtained at different levels of spatial resolution on different observation days. The accuracy rates of the cabbage coverage estimated using an unmixing method from AVNIR-2 and QuickBird imagery were almost the same. This result is very interesting, because it shows that we may be able to evaluate cabbage coverage using remote sensing data obtained at different spatial resolutions on different observation days. Thus, it would be possible to use different remote sensing imagery systems to evaluate cabbage conditions during the growing period using this proposed method.     

Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data

Rats are an important vertebrate pest of oil palm in Malaysia. This damage translates into substantial economic loss to the oil palm plantation sector. We used habitat factors dervived from GIS data to develop a logistic regression model to predict rat occurrence in a FELDA oil palm plantation in Sabah, Malaysia. Our logistic regression results predicted a high occurrence of rats in young palms areas (<3 years) and in areas near the plantation roads. The rat occurrence areas were further examined using a detailed land cover types generated from a high-resolution satellite image (GeoEye, spatial resolution: 0.5 m). Our results showed that the combination of bare or open areas bushes mixed with partial shades of young palms is important to the survival of Rattus rattus diardii, a highly adaptable rat species that dominated the plantation. The combined use of GIS and high-resolution satellite remote sensing techniques enhanced our understanding of rat occurrence in oil palm plantation. Our results suggest these techniques can be used to predict rat occurrence and can be used to guide the rat baiting program in the oil palm plantation.     

Distinguishing blueberry bushes from mixed vegetation land use using high resolution satellite imagery and geospatial techniques

Blueberry orchards for commercial production are increasingly common in Georgia and other southeastern states. The blueberry bushes grow closer to the ground compared to pine trees and other forest plants. It is, therefore, difficult to distinguish blueberry bushes from other trees and shrubs in a farm scenario where tall grasses are abundant and pine trees are in close proximity. The goal of this study was to apply advanced image processing techniques with high resolution multispectral imagery to distinguish blueberries in mixed vegetation. We used high resolution 2.15 m multispectral QuickBird imagery along with high end image processing techniques to identify blueberry bushes of a small orchard, located in Pike County, Georgia. Principal component bands of multispectral QuickBird images, taken on May 22 and June 6, 2006, were classified using an unsupervised ISODATA classification technique and the WARD minimum variance method. Four classes, including forest, blueberry bushes, tall grasses, and cut or dwarf grasses were extracted from the classified images for ground truth and subsequent delineation of spatial cells that represented the blueberry bushes. For the image taken on May 22 the blueberry bushes were distinguished with a 53% producer's accuracy, a 100% user's accuracy, and a kappa statistic of 0.24. This low accuracy was attributed to mixture of the blueberry bushes and the tall grasses that were not cut when the image was acquired. However, the June 6 image proved to be more suitable for distinguishing blueberry bushes from the pine forest and grasses. The producer's accuracy was 100%, the user's accuracy was 94% and the kappa statistic was 0.65. Based on the results from this study it can be concluded that high resolution imagery and high end image processing techniques can be used to help distinguish mature blueberry bushes from a forest and grass land cover if the area is well maintained. The study also suggests that commercial or large scale blueberry orchards can easily be micro-managed with the use of remotely sensed images and geospatial technology.     

黄瓜茎基腐病菌拮抗真菌的分离和筛选

[目的]分离和筛选黄瓜茎基腐病菌的拮抗真菌。[方法]从病田土壤采集21个土壤标本,分离得到5种对瓜果腐霉、瓜类腐皮镰孢菌和立枯丝核菌有拮抗作用的拮抗菌,并进行温室盆栽防病试验。[结果]经鉴定,5种拮抗菌分属于长枝木霉、橘绿木霉、康氏木霉、哈慈木霉和绿色木霉,对瓜果腐霉、瓜类腐皮镰孢菌和立枯丝核菌的生长都有强烈的抑制作用。在人工接种条件下,5种拮抗菌对立枯丝核菌引起的茎基腐病的防效在60%以上,对瓜果腐霉引起的茎基腐病的防治效果差些。[结论]该研究筛选出的5种拮抗菌对瓜果腐霉、瓜类腐皮镰孢菌和立枯丝核菌引起的黄瓜茎基腐病均有一定的防效。     

Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves

Ten, widely-used vegetation indices (VIs), based on mathematical combinations of narrow-band optical reflectance measurements in the visible/near infrared wavelength range were evaluated for their ability to discriminate leaves of 1 month old wheat plants infected with yellow (stripe), leaf and stem rust. Narrow band indices representing changes in non-chlorophyll pigment concentration and the ratio of non-chlorophyll to chlorophyll pigments proved more reliable in discriminating rust infected leaves from healthy plant tissue. Yellow rust produced the strongest response in all the calculated indices when compared to healthy leaves. No single index was capable of discriminating all three rust species from each other. However the sequential application of the Anthocyanin Reflectance Index to separate healthy, yellow and mixed stem rust/leaf rust classes followed by the Transformed Chlorophyll Absorption and Reflectance Index to separate leaf and stem rust classes would provide for the required species discrimination under laboratory conditions and thus could form the basis of rust species discrimination in wheat under field conditions.     

油菜菌核病轻发生条件下的空间分布格局与抽样技术

通过田间调查,应用聚集度指标法、Iwao法和Taylor幂函数法,研究油菜菌核病的田间空间分布格局和抽样技术.结果表明,油菜菌核病空间分布型总体上呈聚集分布,但聚集程度不高,少量田块呈随机、均匀分布.轻发生时油菜菌核病的空问分布型倾向随机和均匀分布.抽样数量随着发病程度的加重而递减,最适理论抽样模型为n2=103.33/m-0.86,在茎株发病率为轻发生的10％时,每田的理论抽样样方数为103,即1030株.     

Classification of oil palm fresh fruit bunches based on their maturity using portable four-band sensor system

Classification of oil palm fresh fruit bunch (FFB) maturity is a critical factor that dictates the quality of produced palm oil. This study evaluates a multi-band portable, active optical sensor system; comprising of four spectral bands, 570, 670, 750, and 870 nm, to detect oil palm FFB maturity. The in-field spectral reflectance data were collected using the sensor system from a total of 120 fresh fruit bunches. These fruit bunches were categories into unripe, ripe, and overripe classes. Different classifiers were applied to assess the applicability of using the sensor system. Based on the classification accuracies, data analysis on the spectral features (reflectance data and other features extracted from vegetation indices) indicated that the spectral reflectance data could be valuable in predicting the maturity of the fruit bunches. The quadratic discriminant analysis and discriminant analysis with Mahalanobis distance classifiers yielded highest average overall accuracies of greater than 85% in classifying oil palm FFB maturity. Additionally, the average individual class (unripe, ripe, and overripe) classification accuracies were also higher than 80%. Thus, optical sensing using four-band sensor system could be useful for oil palm FFB maturity classification under field condition.     

十堰市部分地区魔芋腐烂病发病类型和重要致病菌

为了明确湖北省十堰市魔芋腐烂病的发病类型及重要致病菌,调查了十堰市不同地点魔芋腐烂病的发病类型,研究了不同地区病原菌的分离频率、优势菌种类及致病性。结果表明,魔芋发病率和发病症状因地点而异,可分为茎基环状软腐型、黄化茎基黑烂型、黄化茎黑裂型、黄化茎干软型、黄化茎基外黑内红型、茎上部或整株黒烂型六大类症状。柳陂基地魔芋发病率最高,茎基环状软腐型和黄化茎基黑烂型发病率分别为13.0%和26.9%;郧西乡魔芋发病率最低,为4.8%。从28个样品中共分离到2种真菌和11种细菌,其中真菌为齐整小核菌和镰刀菌,优势细菌为胡萝卜软腐果胶杆菌胡萝卜亚种（Pectobacterium carotovorum subsp. carotovorum）、嗜麦芽寡养单胞菌（Stenotrophomonas maltophilia）和产酸克雷伯氏菌（Klebsiella oxytoca）,分离频率分别为27.6%、17.6%和12.1%。致病性测定表明,胡萝卜软腐果胶杆菌胡萝卜亚种为魔芋软腐病的致病菌。利用胡萝卜软腐果胶杆菌特异性引物仅从被鉴定为该种的B12、B16、B17菌株中扩增出特异DNA条带。上述结果表明：魔芋腐烂病存在复合侵染,胡萝卜软腐果胶杆菌为魔芋腐烂病的重要致病菌,为魔芋腐烂病的防控提供了依据。     

QuickBird satellite versus ground-based multi-spectral data for estimating nitrogen status of irrigated maize

In-season nitrogen (N) management of irrigated maize (Zea mays L.) requires frequent acquisition of plant N status estimates to timely assess the onset of crop N deficiency and its spatial variability within a field. This study compared ground-based Exotech nadir-view sensor data and QuickBird satellite multi-spectral data to evaluate several green waveband vegetation indices to assess the N status of irrigated maize. It also sought to determine if QuickBird multi-spectral imagery could be used to develop plant N status maps as accurately as those produced by ground-based sensor systems. The green normalized difference vegetation index normalized to a reference area (NGNDVI) clustered the data for three clear-day data acquisitions between QuickBird and Exotech data producing slopes and intercepts statistically not different from 1 and 0, respectively, for the individual days as well as for the combined data. Comparisons of NGNDVI and the N Sufficiency Index produced good correlation coefficients that ranged from 0.91 to 0.95 for the V12 and V15 maize growth stages and their combined data. Nitrogen sufficiency maps based on the NGNDVI to indicate N sufficient (≥0.96) or N deficient (<0.96) maize were similar for the two sensor systems. A quantitative assessment of these N sufficiency maps for the V10–V15 crop growth stages ranged from 79 to 83% similarity based on areal agreement and moderate to substantial agreement based on the kappa statistics. Results from our study indicate that QuickBird satellite multi-spectral data can be used to assess irrigated maize N status at the V12 and later growth stages and its variability within a field for in-season N management. The NGNDVI compensated for large off-nadir and changing target azimuth view angles associated with frequent QuickBird acquisitions.     

Devices to detect red palm weevil infestation on palm species

The date palm (Phoenix dactylifera L.) and other palm species have recently been threatened by the red palm weevil (RPW) Rhynchophorus ferrugineus Olivier, which is very difficult to be detected at early stage. This research tested non invasive approaches to detecting RPW including: a TreeRadarUnit? (TRU); a densitometer, a penetrometer used for evaluation of the standing trees stability; a thermal camera and a digital camera. The technologies were applied in Italy on 715 palms (173 P. dactylifera, 453 Phoenix canariensis Chabaud and 311 of other palm species), and on 86 adult date palms in Saudi Arabia. In Italy, the thermal camera showed a high accuracy (96.29%) compared to close visual observation over the following nine months. The digital camera did almost as well (92.57%). Tree Radar Unit and densitometer also showed good accuracy (83.33 and 88.89% respectively). In the Kingdom of Saudi Arabia, the thermal camera showed a good accuracy (77.73%) when compared to invasive diagnosis (i.e. cutting down and opening up palm trunks). The digital camera showed a lower accuracy of 66.67% due to the fact that the red weevil mainly attacks the base of the stem and therefore there are no visible symptoms on the crown shape that would be picked up in image analysis. TRU gave good results (74.73% compared to invasive diagnosis), with the best accuracy at ground level (80.65%). The densitometer results were similar to the TRU case, with higher accuracy (82.26% compared to invasive diagnosis) and the highest at ground level (87.10%).     

Using high spatial resolution satellite imagery for mapping powdery mildew at a regional scale

Efficient crop protection management requires timely detection of diseases. The rapid development of remote sensing technology provides a possibility of spatial continuous monitoring of crop diseases over a large area. In this study, to monitor powdery mildew in winter wheat in an area where a severe disease infection occurred, the capability of high resolution (6 m) multi-spectral satellite imagery, SPOT-6, in disease mapping was assessed and validated using field survey data. Based on a rigorous feature selection process, five disease sensitive spectral features: green band, red band, normalized difference vegetation index, triangular vegetation index, and atmospherically-resistant vegetation index were selected from a group of candidate spectral features/variables. A spectral correction was processed on the selected features to eliminate possible baseline effect across different regions. Then, the disease mapping method was developed based on a spectral angle mapping technique. By validating against a set of field survey data, an overall mapping accuracy of 78 % and kappa coefficient of 0.55 were achieved. Such a moderate but practically acceptable accuracy suggests that the high resolution multi-spectral satellite image data would be of great potential in crop disease monitoring.     

杉木立木腐朽病的初步调查

对杉木立木腐朽病的症状类型、病原菌及发病条件进行了调查分析。结果表明,其发病部位主要在杉木根茎部和树干基部,腐朽表现为心材腐朽、边材腐朽和心材边材共腐朽3种类型;引起病害的病原菌为Eu-rophiumsp.和Geotrichumsp.;病菌的侵入途径是伤口。因此,建议在杉木营林和护林过程中减少伤口的形成,以控制病害的发生。     

南充油菜菌核病发生流行成因分析及综合防控措施研究

对1998——2008年油菜菌核病田间系统调查和病情普查分析表明,南充市油菜菌核病具有单年流行的菌源量基数和长达18～25天的病菌孢子最适侵染期,而适宜的气象条件则是菌核病重发的决定性因素.根据11年来2-4月的气象因子,结合最终茎秆发病面积比、最终茎病株率和最终病情指数建立了3个数学模型,并取得较好回检效果.利用稻草覆盖、适当调整播栽期等轻简化栽培控病措施,对油菜菌核病的综合防治效果可达50%以上;用2次50%多菌灵100 g/667m<''2>防效可达85%以上,菌核病在南充尚未对多菌灵产生明显的抗药性.     

广州地区西洋杜鹃根腐与茎基腐病病原种类鉴定

 西洋杜鹃是近些年广东新引进的一种重要盆栽花卉,但根腐和茎基腐发生严重,常造成大量死亡。通过病组织分离、接种试验及病原菌鉴定,结果表明该病是由帚梗柱孢霉（Cylindrocladium scoparium Morgan）、烛台帚梗柱孢霉（C.candelabrum Viegas Bragantia ）和柑橘褐腐疫霉［Phytophthora citrophthora (R. E. Smith) Leonian］引起。当Cylindrocladium spp.与P. citrophthora复合侵染时,其发病程度更为严重。     

广西花生茎腐病及青枯病的发生与防治

总结广西花生茎腐病、青枯病的侵染途径、症状表现,有针对性地提出了防治对策,以为花生茎腐病、青枯病的防治提供参考。     

利用油菜花瓣实验检测油菜菌核病

摘要：油菜菌核病是由Sclerotinia sclerotiorum (Lib) de Bary引起的,是世界范围内造成损失最严重的病害之一。该病害主要通过感染了核盘菌子囊孢子的花瓣落在植株茎、叶上来侵染植株。本实验采用添加了两种不同PH指示剂的改良型Steadman’s培养基检测被子囊孢子感染的花瓣,样品采自合肥的两块不同试验田,在油菜花期（3月下旬～4月中旬）每天采摘新鲜花瓣在室温下培养,结果表明整个花期,除1块田1天没有检测出外,其余每天都有被子囊孢子感染的花瓣出现（感染子囊孢子的花瓣接种后培养基变色）。油菜初花期被子囊孢子感染的花瓣较少,而盛花期和终花期被感染的花瓣较多,第一块田被感染的花瓣数在两种培养基上出现的百分率分别为32.0％和40.2％,第二块田分别为27.3％和35.7％。第一块田油菜菌核病的发病率和病指分别为2.7％和1.8,第二块田分别为1.5％和0.4。子囊孢子感染的花瓣数与后期油菜菌核病的发病率呈显著正相关（r=0.829,r0.05=0.811）。研究被感染的花瓣数可以帮助决定最适宜的病害防治时期。