Nitrogen Nutrition Index and Its Relationship with N Use Efficiency, Tuber Yield, Radiation Use Effi ciency, and Leaf Parameters in Potatoes

Knowledge about crop growth processes in relation to N limitation is necessary to optimize N management in farming system. Plant-based diagnostic method, for instance nitrogen nutrition index （NNI） were used to determine the crop nitrogen status. This study determines the relationship of NNI with agronomic nitrogen use efficiency （AEN）, tuber yield, radiation use efficiency （RUE） and leaf parameters including leaf area index （LAI）, areal leaf N content （NJ and leaf N concentration （N0. Potatoes were grown in field at three N levels： no N （N 1）, 150 kg N ha^-1 （N2）, 300 kg N ha^-1 （N3）. N deficiency was quantified by NNI and RUE was generally calculated by estimating of the light absorbance on leaf area. NNI was used to evaluate the N effect on tuber yield, RUE, LAI, NAL, and NL. The results showed that NNI was negatively correlated with AEN, N deficiencies （NNI〈 1） which occurred for N 1 and N2 significantly reduced LAI, NL and tuber yield; whereas the N deficiencies had a relative small effect on NAL and RUE. To remove any effect other than N on these parameters, the actual ratio to maximum values were calculated for each developmental linear relationships were obtained between NNI and tuber RUE to NNI. stage of potatoes. When the NNI ranged from 0.4 to 1, positive yield, LAI, NL, while a nonlinear regression fitted the response of

Weed Recognition Using Image-Processing Technique Based on Leaf Parameters

Weeds normally grow in patches and spatially distributed in field. Patch spraying to control weeds has advantages of chemical saving, reduced cost and environmental pollution. Advent of electro-optical sensing capabilities has paved the way of using machine vision technologies for patch spraying. Machine vision system has to acquire and process digital images to make control decisions. Proper identification and classification of objects present in image holds the key to make control decisions and use of any spraying operation performed. Recognition of objects in digital image may be affected by background, intensity, image resolution, orientation of the object and geometrical characteristics. A set of 16, including 11 shape and 5 texture-based parameters coupled with predictive discriminating analysis has been used to identify the weed leaves. Geometrical features were indexed successfully to eliminate the effect of object orientation. Linear discriminating analysis was found to be more effective in correct classification of weed leaves. The classification accuracy of 69% to 80% was observed. These features can be utilized for development of image based variable rate sprayer.

Effects of Different Water and Fertilizer Combinations on Tree Structure,Leaf Parameters and Photosynthesis of Apple Saplings

[ Objective] This study aimed to investigate the effects of different water and fertilizer combinations on apple saplings. [ Method] ＇ Tianhong 2＇ Fuji /SH40/Malus robusta Rehd. was used as the experimental material to analyze the effects of different irrigation modes and combinations of basal fertilizer and dressing fertilizer on tree structure, leaf parameters and photosynthesis of apple saplings. [ Result] The results showed that different water and fertilizer combinations ex- hibited varying effects on tree structure, leaf parameters and photosynthesis of apple saplings. To be specific, applying 432 000 kg/hm2 basal fertilizer, 480 kg/hm2 urea and 915 kg/hmz organic fertilizer ＋ 0 ＋ 915 kg/hm2 organic fertilizer as dressing fertilizer, and 1% urea as leaf fertilizer was conducive to promoting growth of branches and leaves, increasing leaf thickness, individual leaf area and SPAD, and improving photosynthesis of apple saplings under half root irrigation and whole root irrigation conditions. In addition, the effects were more significant under whole root irrigation conditions. [ Conclusion] Selecting the appropriate water and fertilizer combination is conducive to the growth of apple saplings.

Relationships between leaf color changes,pigment levels,enzyme activity,photosynthetic fluorescence characteristics and chloroplast ultrastructure of Liquidambar formosana Hance

Liquidambar formosana Hance is an attractive landscape tree species because its leaves gradually change from green to red,purple or orange in autumn.In this study,the red variety of L.formosana was used to establish a quantitative model of leaf color.Physiological changes in leaf color,pigment levels,enzyme activity,photosynthetic fluorescence characteristics and chloroplast ultrastructure were monitored.The relationship between leaf color and physiological structure indices was quantitatively analyzed to systematically explore the mechanisms behind leaf color.Our data showed that with a decrease in external temperatures,chloroplast numbers and sizes gradually decreased,thylakoid membranes became distorted,and chlorophyll synthesis was blocked and gradually decreased.As a result,chloroplast membranes could not be biosynthesized normally;net photosynthesis,maximum and actual photochemical efficiency,and rate of electron transfer decreased rapidly.Excess light energy caused leaf photoinhibition.With intensification of photoinhibition,leaves protected themselves using two mechanisms.In the first,anthocyanin synthesis was promoted by increasing chalcone isomerase and flavonoid glycosyltransferase activities and soluble sugar content so as to increase anthocyanin to filter light and eliminate reactive oxygen species to reduce photoinhibition.In the second,excessive light energy was consumed in the form of heat energy by increasing the non-photochemical quenching coefficient.These processes tuned the leaves red.