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Abstract Assimilate partitioning may contribute to improvements in crop productivity by: a) Increasing total biomass production. Watson (99) drew attention to the subsequently well-qualified observation that assimilate partitioning patterns that favor rapid generation of leaf surface contribute significantly to both genetic- and environmentally induced differences in crop growth rates (87). b) Favoring assimilate transfer to the harvestable portion of the crop. Retrospective physiological analyses have demonstrated that shifts in assimilate partitioning pattern largely account for the evolutionary increase in yield of a range of crop species (for reviews, see ref. 37). Clearly, upper limits exist to the degree to which assimilates may be partitioned to the harvestable portion without jeopardizing the capacity of the plant to support the yield component both structurally and nutritionally. Nevertheless, in these cases, further potential exists for improvement through optimization of yield quality, which, in part, depends on the chemical nature of the assimilate partitioned to the harvested organ.
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A study was conducted to determine the effectiveness of using various doses and modes of pre-sowing electron irradiation of barley of the Vladimir variety as a way to improve the quality and quantity of grain crops. A vegetation experiment was carried out, as a result of which the following crop parameters were evaluated: the height of plants with an ear, the total number of stems, the number of productive stems, the mass of straw, the mass of 1000 grains and crop productivity. New information has been obtained on the formation of biological effects in agricultural crops under the influence of various modes and doses of electronic radiation on its seeds.
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An attempt has been made to study the impact of variability and trend of rainfall on crop production and productivity of different crops at two rain shadow districts of Chhattisgarh state viz. Rajnandgaon and Kawardha by using long term rainfall (1963-2015) and crop (2000-2014) data. An average annual rainfall of 1104 mm and 984 mm has been observed in Rajnandgaon and Kawardha districts respectively and annual CV varies between 14 % and 18 %. It can be concluded from the analysis that the main rainy months in all the stations were during June to September with least variability. In other months, the rainfall was very less and corresponding CV was more than 100 % in all the stations. High rainfall variability indicates its effect which may lead to instability in the crop productivity. Rice and gram are the predominant crops and it shows an increasing trend of productivity in both the districts. Productivity trend for rice crop was increasing @ 54.5 kg/ha/yr and 46.6 kg/ha/yr and chickpea was increasing @ 25.6 kg/ha/yr and 30.6 kg/ha/yr in Rajnandgaon and Kawardha districts respectively. The area and production of soybean crop showed a statistically significant increasing trend but increasing productivity trend was not significant. The area, production and productivity trend of Pigeonpea crop was showing a non-significant value for both the districts. The trend analysis of sugarcane crop showed a significant increasing trend in Kawardha district.
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The main crop potential productivity of Guizhou was calculated by means of the formula,which was introduced by Ho Guang-liang and etc.The results showed:(i) the main crop potential productivity of Guizhou ranged from 3486.5 kg/ha to 19 653.7kg/ha for rice, the average yield of different crop was 11 247.5 kg/ha for maize,16 264.3kg/ha for rice,4744.6kg/ha for rapeseeds and 7161.9 kg/ha for wheat,respectively ;(ii) the main crop potential productivity in the east, north and south-east of Guizhou was higher, that in the middle and south-east of Guizhou was mean and that in north-west of Guizhou was lower; (iii) compared with the actual yield, crop potential increasing rate of Guizhou was 5.0 %-23.0 % in recent period and 29.6 %-55.9 % after a rather long time;(Ⅳ)food security of Guizhou could be guaranteed only by enforcing practices of increasing yield and quality of crop.
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Fifteen lab exercises in field crop production or crop science. Includes coverage of the basic exercises and materials, such as seed/grain anatomy and seedling development; seed, grass, and legume identification; crop and disease identification. Encourages hands-on involvement through some special f
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Based on the data of grain crop productivity in 14 districts of Gansu province,the spacial difference of the main three grain crop(i.e. wheat,maize and potato)had been discussed,to understand the heterogeneity of grain crop productivity of each district in Gansu province. The results showed that the grain crop productivity was significantly differed in different districts in Gansu province,the main production region of grain crop productivity changed from west part to east part of Gansu province,as well as changed from irrigation area to rain-fed area. The planting area of wheat decreased sharply from 1991 to 2012,the maize and potato increased year by year. Consequently,the structure of grain crop and planting area changed significantly in the past 21 years,and the benefit of grain crop productivity is the main reason which drives this changing.
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A laboratory exercise was initiated using the computer crop model, PNUTGRO, for peanut (Arachis hypogaea L.) during the introductory crop science course at the University of Georgia. The objectives of this study were to determine the computer competency of the students, introduce crop modeling, and determine if students perceive they acquire a better understanding of factors influencing crop production practices by using a computer crop model. Ninety six percent of the students stated that the computer crop model was effective in helping them comprehend factors that affect crop production. Ninety-eight percent of the students stated they would use the model if they were peanut producers themselves. Ninety-three percent indicated that the exercise should continue and of those students, 71% stated future labs should include more crop modeling exercises. Crop modeling proved to be perceived by students as an effective tool for teaching factors influencing crop production.
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The study was conducted in order to estimate the po st-harvest losses in tomato crop produced in Peshaw ar valley during Kharif 2006. Data were collected randomly from sixt y eight tomato growers in the area. The post-harves t losses of tomato crop in Peshawar valley were estimated 20% of the t otal production. There losses mainly occurred durin g picking of the crop, during handling and transportation to the mar kets, etc. To reduce these losses, farmers of the a rea need to be trained about the latest techniques of packaging, processin g of tomato crops, advanced techniques and methods of post-harvest handling.
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