Regionalization for large area crop estimates by remote sensing

The crop estimates by remote sensing, developing quickly in recent decades, is a up-to-date technique. Regionalization for large area crop estimates by remote sensing, a special applied regionalization, is the foundation of crop estimates in a large area by remote sensing. According to the actual demands of wheat yield estimation by remote sensing and wheat agroclimatic demarcation of China, this paper first puts forward some principles upheld in this regionalization and analyses its main bases. Secondly, it works out the classificatory schemes about the optimum temporal for estimating wheat yield by remote sensing, information sources of space remote sensing and landuse structure in China. Finally, According to the regionalization indices, this study divides the wheat plantable region of China into 14 regions of crop yield estimates and 31 subregions of crop yield estimates.     

STUDY ON THE INTERACTION BETWEEN NDVI PROFILE AND THE GROWING STATUS OF CROPS

Daily and ten-day Normalized Difference Vegetation Index(NDVI) of crops were retrieved from meteorological statellite NOAA AVHRR images ,The temporal variations of the NDVI were analyzed during the whole growing season,and thus the principle of the interaction between NDIV profile and the growing status of crops was discussed,As a case in point,the relationship between integral NDVI and winter wheat yield of Henan Province in 1999 had been analyzed.By putting integral NDVI values of 60 sample counties into the winter wheat yield-integral NDVI coordination,scattering map was plotted. It demonstrated that integral NDVI had a close relation with winter wheat yield.These relation could be described with linear,cubic polynomial ,and exponential regression,and the cubic polynomial regression was the best way,In general ,NDVI reflects growing status of green vegetation ,so crop monitoring and crop yield estimation could be realized by using remote sensing technique on the basis of time serial NDVI data together with agriculture calendars.     

TEMPORAL TRENDS IN SOIL PRODUCTIVITY EVALUATIONS*

Studies of soil productivity must compensate for the effects of temporal trends in order to examine the pattern of crop yields along spatial gradients. An analysis of the published yield estimates for 30 soils in 233 counties, however, did not find consistent yield increases over the past three decades. On the contrary, the yield estimates for many soils were markedly uniform since 1972. The uniformity appears to have two causes: the acknowledged difficulty of making yield estimates in a time of increasing variability in soil and crop management, both within and between regions, and surveyors' awareness of data stored in a national soils data base. The effect is to cast doubt on soil productivity data reported in county soil surveys published between 1973 and 1988.     

Water use, growth and yield of green gram under rainfed upland crop sequences in Gangetic Plains of Indian sub-tropics

A field experiment was conducted to study the effect of different crop sequences on water use, growth and yield of green gram (Vigna radiata (L) Wilezek) during 1992-93 and 1993-94 under rainfed upland condition in Indo-Gangetic plains of West Bengal. Green gram sown in the month of March as pre-rainy (summer) season crop, as and when the winter crops vacated the land, produced highest dry matter of 372 gm-2 which was significantly highest in black gram-yellow sarson sequence.The results of the field experimentation revealed that green gram gave highest grain yield to the extent of 10.80 q/ha when sown after black gram (rainy season) followed by yellow sarson (winter season) while the crop produced 10.63 q/ha under sesame-yellow sarson sequence. Highest water use of 267mm was achieved in green gram under black gram-yellow sarson sequence and the crop gave water use efficiency of 4.07 kg ha-1mm-1 under black gram-yellow sarson sequences.     

Water use, growth and yield of green gram under rainfed upland crop sequences in Gangetic Plains of Indian sub-tropics

A field experiment was conducted to study the effect of different crop sequences on water use, growth and yield of green gram (Vigna radiata (L) Wilezek) during 1992-93 and 1993-94 under rainfed upland condition in Indo-Gangetic plains of West Bengal. Green gram sown in the month of March as pre-rainy (summer) season crop, as and when the winter crops vacated the land, produced highest dry matter of 372 gm-2 which was significantly highest in black gram-yellow sarson sequence. The results of the field experimentation revealed that green gram gave highest grain yield to the extent of 10.80 q/ha when sown after black gram (rainy season) followed by yellow sarson (winter season) while the crop produced 10.63 q/ha under sesame-yellow sarson sequence. Highest water use of 267 mm was achieved in green gram under black gram-yellow sarson sequence and the crop gave water use efficiency of 4.07 kg ha-1mm-1 under black gram-yellow sarson sequences.     

我国部分市郊农田的重金属污染与防治途径

分析了我国部分主要城市农田土壤及农作物重金属污染状况，以了解土壤中与农作物中重金属污染物间的相互关系、变化趋势及造成污染的影响因素。结果表明，我国各大城市的农田土壤及农作物都存在不同程度的重金属污染，北方地区的土壤及农作物受重金属污染程度普遍高于南方。重金属在农作物与土壤中的含量一般呈正相关关系，受多种因素影响。对于已污染的土壤，可采用农业工程措施、生物修复法和施用改良剂等予以治理。     

农产物产量预报模式管理应用系统的软件设计

为更加系统有效地开展农作物产量预报工作，研制了《农作物产量预报模式管理咨询应用服务系统》，可将各种类型的已建产量预报模式归入档入库，为用户提供咨询服务并自动实现预报结果输出     

PELIMINARY ANALYSES FOR CROP WATER CONSUMPTION BY USING LYSIMETER

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ASSESSING THE SUITABILITY OF THE EPIC CROP MODEL FOR USE IN THE STUDY OF IMPACTS OF CLIMATE VARIABILITY AND CLIMATE CHANGE IN WEST AFRICA

The EPIC (Erosion Productivity Impact Calculator) crop model, developed by scientists of the United States Department of Agriculture (USDA), has been successfully applied to the study of erosion, water pollution, crop growth and production in the US but is yet to be introduced for serious research purposes in other countries or regions. This paper reports on the applicability of the EPIC 8120 crop model for the assessment of the potential impacts of climate variability and climate change on crop productivity in sub‐Saharan West Africa, using Nigeria as the case study. Among the crops whose productivity has been successfully simulated with this model are five of West Africa's staple food crops: maize, millet, sorghum (guinea corn), rice and cassava. Thus, using the model, the sensitivities of maize, sorghum and millet to seasonal rainfall were demonstrated with coefficients of correlation significant at over 98 per cent confidence limits. The validation tests were based on a comparison of the observed and the model‐generated yields of rice and maize. The main problems of validation relate to the multiplicity of crop varieties with contrasting performances under similar field conditions. There are also the difficulties in representing micro‐environments in the model. Thus, some gaps appear between the observed and the simulated yields, arising from data or model deficiencies, or both. Based on the results of the sensitivity and validation tests, the EPIC crop model could be satisfactorily employed in assessing the impacts of and adaptations to climate variability and climate change. Its use for the estimation of production and the assessment of vulnerabilities need to be pursued with further field surveys and field experimentation.     

Growth response of the saltbush Atriplex nummularia L. to inoculation with the arbuscular mycorrhizal fungus Glomus intraradices

Plantlets of Atriplex nummularia were inoculated with the arbuscular mycorrhizal fungi Glomus intraradices in a pot experiment. Plants were grown in a low P soil. Highly significant growth response of a Chenopodiaceae was recorded for the first time. Mycorrhizal colonization of roots was well developed, internal hyphae and vesicles were observed, but not arbuscules. These observations suggest that arbuscules are not necessary to obtain significant growth stimulation from mycorrhizal inoculation. Atriplex nummularia is already used as forage crops, its high mycorrhizal dependency offers possibilities to develop this production and revegetation strategies.