Spectrum of the Pests on Cereal Crops and Influence of Soil Fertilisation

Different biotic factors such as predators, parasitoids and different pathogens affect the pests of cereals. Also affecting them are the abiotic factors temperature, rainfall, humidity, wind and sunshine (Sehgal 2006).

Climatically, the slowly rising temperatures are very important for the spectrum of pests. Winters are shorter, temperatures below freezing occur on average on fewer days than before and the soil is frozen to shallower depths. This results in pest species occurring at northern localities, whereas  before they had appeared only at lower latitudes (Gallo 2002).

Past research has shown that fertilisation of the soil affects a pest’s presence. Fertilisation had a positive effect on the crops, especially on their height and density, leading to a higher presence of pests. Stimulation of plant growth and development is the main goal of fertilisation. Regeneration of the plants is important if the pests damage the plants.

Organic fertilisation is very important because it suppresses the plant pathogens and also affects the frequency of pests (Sokolov 1991). Healthy vital plants are preferred by many pests on cereal species (Price 1991; Breton & Addicott 1992; Preszler & Price 1995).

The variety of a crop can also affect the occurrence of a pest. Ovipositonal behaviour, variability of eggs, growth and survival of the young larvae of the cereal leaf beetle were adversely affected by the trichome density on wheat leaves(Schillinger& Gallun 1968). Eggs per plant and larval survival decreased asthe length and density of trichomes increased (Hoxie et al. 1975).

Differences in the yields between the varieties and the year’s volume in the same level of the damage were detected. Later varieties were better able to compensate for the damage than earlier varieties in years with similar weather (Šedivý 1995).

Influence of a new farming system on pests and their natural enemies has began a few years ago (Khamraev 1990; Pfiffner 1990; Xie et al. 1995).

Material And Methods

Our research was conducted at Nitra-Dolná Malanta. The whole area (530 m2 ) used in the tree-year experiment (2004–2006) was split into 8 identical plots (each of 60 m2 ) separated by a 1 m belt where soil was superficially cultivated.

Pests were monitored on spring barley cvs. Jubilant (2004) and Annabell (2005, 2006), and on winter wheat cvs. Samanta (2004) and Solara (2005, 2006). At every sampling date 5 m2 of winter wheat and spring barley was swept using a standard sweeping net. Collecting began at the shooting phase, ended at wax ripeness of cereal crops and was done every 7–10 days, depending on the weather.

The insects collected from each crop were determined. Spiders were removed from samples, and aphids were excluded from the analysis at they were used in another study. We determined the influence of fertilisation and nutrition on the pests in the control variants(0) without fertilisation, and variants fertilised (F) with manure (40 t/ha) + fertilisers(winter wheat for 7 t yield: 70 kg N/ha, 30 kg P/ha, 0 kg K/ha; spring barley for 6 t yield: 30 kg N/ha, 30 kg P/ha, 0 kgK/ha).Climatic data were provided by the meteorological station nearthe Slovak University of Agriculture at Nitra, Slovak Republic. All results were evaluated with mathematical-statistic analysis Statgraphics.

Results and disscusion

Spring barley

In 2004, insects were first collected in the last decade of April; during next 2 years collecting began in the first decade of May. The beginning of collecting was affected by the weather during the years. The last insects occurred in the first decade of July. The date of the maximum occurrence of the pests changed during the research. Maximum of the insects was recorded between the May and (307pieces/5m2 ) a June (357pieces/5 m2) in 2004.The abundance of the insects decreased at about 45% after this time. The lowest abundance of insects was in May during the low average day temperatures. Maximum occurrence of total insects was in the last decade of May and in the first decade of June. Our results are similar to results of Gallo (2002), who maximum of the insects recorded in the first decade of May and June. Only one maximum of occurrence was recorded in 2004.Only one maximum was recorded in 2006 too. Two maximum of occurrence were recorded in 2005.

The maximum occurrence of the pests(89 pieces/5 m2 ) was recorded on spring barley at the beginning of the June in 2006. Phyllotreta (18 pieces/5m2 ), Thysanoptera (21 pieces per 5 m2 ) and Oulema gallaeciana (12 pieces/5 m2 )were dominant pests. Other authors presented the same spectrum of dominant pests (Gallo & Pekár 1999). There were no insects recorded on spring barley in July. The spring barley was in the wax ripeness. Abundance of the natural enemies increased at about 28% in the second decade of June but it decreased compared to the first decade about 80% by the end of month.

Different occurrence of the insectswasin20.The maximum of the collected insects (102 pieces per 5 m2 ) was at the end of June. The total number of insects 114 pieces/5 m2 was recorded in the first decade of June and from which there were 84pieces/5m2 pests. There was recorded maximum amount of natural enemies(14 pieces/5 m ). The second maximum of total insects(262 pieces/5m2) and also pests (177 pieces/5 m2 ) was recorded in the last decade of May. The collecting was realised in the first decade of July in 2005. The amount of the pests decreased at about 34% and natural enemies at about 63% in 2005. During the three years study the effect of fertilisation was monitored in the spring barley (Figure 2).According the results, more pests were recorded on fertilised variants.The more pests were recorded on the non-fertilised variants only in 2004. Our results are different from results of Samsonova (1991), according which the fertilisation had no effect on the occurrence of the pests. Levine (1993) results are similar to ours.

The occurrence of the insects had the similar character on fertilised and non-fertilised variants. The relation between fertilised and non-fertilised variants had not statistically significant difference

Total amount of collected insects on spring barley had increasing tendency during the all years. Total amount of the pests was 1630 pieces per 5 m2 collected during the entire period in2004.

This number decreased at about 55%in 2006.The amount of natural enemies had also decreasing tendency. While 66 pieces/5 m2 of natural enemies were collected in 2004, this amount decreased at about 67% in 2006 (Table 1). This drop could be caused by higher temperature during the year 2006.

According to Honěk (2003), McAvoy and Kok (2004), the temperature influenced occurrence and development of the pests in crops. Difference between the year 2004 and the other years 2005 and 2006 was statistically evident.

Winter wheat

The beginning of collecting was realised in the second decade of April and the last collections were realised in the first decade of July during the years 2004–2006.The last collection was realised atthe end of June in 2006.The beginning was affected by the weather during the years.

The first maximum of the pests was recorded in the last decade of April(247 pieces/5 m2 )in 2004. The second maximum was recorded at the end of May (350 pieces/5 m2 ) and at the beginning of June(285 pieces/5 m2 ).Thrips (44 pieces/5 m2 ) had the highest occurrence. The cereal leaf beetle was recorded at most in April. It was found occasionally in the crops in the next time. Aphids(58 pieces/5 m2) were recorded in the crops in June. Maximum occurrence of the pests was recorded in the last decade of May (284 pieces/5 m2 ), the second one in the second decade of June (314 pieces/5 m2 ) in 2005. There were trips (26 pieces/5 m2 ) and flea beetle (38 pieces/5 m2 ) and also cereal leaf beetle(15 pieces/5 m2).The aphids were not recorded in this year. During the terms with the highest level of the pests, there were also recorded the highest occurrence of the natural enemies (53pieces/5 m2).

Our results were similar to the results of Gallo and Pekár (1999, 2001),which presented the same spectrum of the pests. The high occurrence of the pests was recorded also in the first(266 pieces/5 m2) and in the second (197 pieces/5 m2 ) decade of June. The highest occurrence had again thrips (18 pieces per 5 m2 ), flea beetle (24 pieces/5 m2) and cereal leaf beetle (10 pieces/5 m2). Frittfly Oscinella fritt was recorded (6 pieces/5 m2) during the entire year.

The higher occurrence ofthe pests could be caused by higher temperature during the year. According to Petr et al. (1987), and McAvoy and Kok (2004), the temperature influenced occurrence and development of the pests in the crops. The influence of the fertilisation was study during three years research on winter wheat.

According to our results, the higher occurrence of the pests was recorded on fertilised variants. The higher occurrence of the pests was recorded on the non-fertilised variants only in the year 2004. Our results are different from the results of the other author according which the fertilisation had no influence at the pests (Samsonova 1991).The similar results reached Levine (1993) and Gallo and Pekár (1999).The occurrence of the insects had the similar character on fertilised and non-fertilised variants. Maximum amount of the pests was recorded one decade sooner on the fertilised variants than on the non-fertilised variants. Relation between fertilised and non-fertilised variants had not statistically significant difference.

The total number of insects had a decreasing tendency during the three years and in both variants of fertilisation. While 3259/5 m2 of insects were collected in 2004, this number decreased by about 51% in 2006. This decrease was expressive on the non-fertilised variantsin 2006, it began on the fertilised variants after the first year. The same decreasing tendency had also pests and their natural enemies. Their occurrence decreased at about 59%during the study. Difference between the year 2006 and the other years 2005 and 2004 was statistically evident.

(Source –  http://www.agriculturejournals.cz/publicFiles/01158.pdf)

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“More” compared with…?

There is obviously a wide variety of no-till farming systems and so there is an equally wide variety of conventional tillage based agricultural systems. The use of herbicides is a common feature and widespread practice in many intensive farming systems. This applies equally to tillage based conventional farming as to no-till farming. Herbicides are a useful tool for weed management, particularly in the first years after shifting from conventional farming to no-till farming. It is much easier, to do no-till farming with herbicides than without.  If now no-till farming is introduced in an environment of traditional peasant farming, where no herbicides are used at all, these no-till farming systems will obviously use “more” herbicides than the traditional conventional systems.

However, in many conventional systems herbicides are already frequently used and mechanical weed control has nearly disappeared in intensive farming. In such a system, the shift to no-till farming might not necessarily increase the use of herbicides dramatically. Even where it does increase the amount of active ingredient applied per area and year, the environmental impact is not necessarily worse, as often there is a shift from herbicides with relatively high environmental impact to other herbicides with less impact.

Therefore, it is difficult to generalize and no-till farming systems might not always require more herbicides than conventional farming systems.

What are the conditions for increased herbicide use under no-till?

Nevertheless, most of the scientific literature shows that notill farming does in fact require more herbicides than conventional systems comparing similar cropping systems.

There is no doubt that there are significant areas under notillage systems, where herbicide overuse is creating environmental problems. These systems are characterized by monocultures and, in absence of soil tillage, by herbicide use being the only weed management strategy applied. These areas are the ultimate proof for the statement, that no-till farming uses more herbicides. Many of these areas are also cropped with genetically modified crops, which are resistant to a specific herbicide. Therefore, the herbicide use in these cases is restricted to a single product. However, under such a condition, even soil tillage would not really improve the herbicide use. Such cropping systems, with or without tillage, can be considered as not conforming to good agricultural practice.

What is the weed control effect  of tillage?

Soil tillage has been developed for a number of reasons, such as to facilitate the preparation of a seedbed for a more efficient seeding. However, weed control has always been attributed to soil tillage and, particularly, the development of the mouldboard plough was very effective for weed management. But, in the long term, the weed control effect of tillage has proven to be insufficient and herbicides have become the tool of choice in intensive farming. The problem of tillage is that by creating a good seedbed for the seeds, it creates the same conditions for the weeds. While weed seeds are buried deeply with the mouldboard plough, the same plough brings to the surface the weed seeds that had been buried the season before. The seed bank in most agricultural soils is probably large enough that the plough does not have a long lasting control effect on weeds which multiply by seeds. On the other side, weeds propagating through sprouts or roots can even be multiplied by tillage implements, which only cut and mix them with the soil, so that the number of potential weed plants is increased. Through soil carried with tillage implements from one field to another, the weed population is also spread throughout the entire farmland.

Therefore, the use of tillage for weed control is not the ultimate answer, nor is the move to no-till the ultimate doom in terms of weed control.

How can herbicide use be  reduced?

This brings us back to herbicides. In all farming situations, not only in no-till farming, the use of herbicides can be reduced by applying the products correctly, using the right equipment with the appropriate settings under optimal conditions. Often the application of herbicide is done with even less care than the application of other pesticides, as herbicides are usually considered less toxic than, for example, insecticides. It leads then to increased application rates as the product is not reaching the target, but is wasted in the environment. This can become a problem, where herbicides have not been used traditionally and where, therefore, there is no appropriate equipment available for the application of herbicides once more intensive farming systems are introduced. For example, in the case of Uzbekistan, farmers start using the existing air blast sprayers, which are traditionally used for application of defoliants in cotton, for herbicide application. Similar cases can be found in other

Central Asian countries, such as Mongolia or Kazakhstan, where frequent cultivation of black fallow has been the only weed management strategy for the past few years and where the spray rigs are sometimes in very bad conditions. In FAO projects carried out in these countries, the simple upgrade of existing sprayers with upgrade kits, comprising pumps, controls, hoses and nozzles, reduced the herbicide use compared to farmers practice before the upgrade by 10 to 15 % while the weed control efficiency was at the same time improved by 20 % to values above 90 % control.

What are alternatives for weed management under no-till?

However, the main question remains, whether there are any alternative strategies for weed control that are applicable in no-till farming systems and which would allow reducing the dependency on herbicides. There is actually a wide range of options and principles within a weed management strategy that allow managing weeds without tillage and herbicides.

This starts with a forward looking strategy of weed control, to avoid the maturation and seeding of weeds in the first place by not allowing weed growth even in the off season. Applying this strategy, the farmers in an FAO project in Kazakhstan noticed after only two years of no-till cropping without even using a diversified crop rotation that the weed pressure and, hence, the need for herbicide use was being reduced compared to the conventional tillage based systems.

Another general point is to determine, at which point weeds are actually damaging the crop. It is often not necessary to eradicate the weeds completely, but only to avoid the setting of seeds and competition with the crop. Leaving weeds in a crop at a stage where the crop can suppress them and where there is no damage or problem for the harvest can actually help with managing other pests, such as termites or ants, which in absence of weeds would damage the crop.

A second aspect comes from the soil tillage itself. Farmers who do no-till for several years will notice that weed germination is reduced where the soil is not touched. Once the superficial weed-seed bank is depleted and no new seeds are added, the other seeds still remaining in the soil will not germinate as they will not receive the light stimulus for germination. For this reason, the no-till planters from Brazil,

for example, where no-till farming is reaching nearly 50 % of the total agricultural area, are designed to avoid any soil movement and to cover the seed slot immediately with mulch to create an “invisible” no-till seeding. This is done to reduce the emergence of weed seeds

The most powerful no-tillage and non-chemical weed control in no-till systems, however, is soil cover and crop rotation. Maintaining the soil covered with an organic mulch or a live crop can allow, under certain conditions, notill farming without using any herbicide. For this purpose, it is important to know the allelopathic effects of cover crops. These effects result from substances in the plants which can suppress other plant growth. Cover crops are crops which can be grown between commercial crops to maintain permanent soil cover. Crop rotations have to be designed in such a way, that the soil is always covered and that the variety of crops in the rotation facilitates the management of weeds. For managing the cover crops, a knife roller is used, which breaks the plants and rolls them down.

Applied at the right time, this tool can actually kill some of the cover crops without need of herbicide and achieve complete weed control throughout the next cropping season, provided the planting is done with minimum soil movement. Applying a knife roller, for example, in a well developed cover crop of black oat (Avena strigosa) at milk stage, will completely kill the cover crop, which on the other side will provide good weed control. In Brazil after a cover crop of black oat, there is usually no additional herbicide applied for the following crop There is a lot of scientific and practical evidence that weed infestation under no-till farming using certain cover crops and diversified crop rotations is declining in the long term, allowing a similar decline in herbicide use. Farmers using these principles of good agricultural practice in no-tillage systems report declining pesticide use in general, which also includes declining herbicide use at a level lower than comparable conventional systems.

Starting no-till farming with the establishment of good cover crops and a forward looking weed management allows the introduction of no-till farming in small holder farms in Africa without any herbicide use at all and with a reduction of manual weeding requirements. Spectacular effects were achieved in an FAO project in Swaziland using no chemical inputs and increasing both yields and reducing the drudgery of farm work by introducing a no-till farming system combined with permanent soil cover and crop rotation better known as Conservation Agriculture.


There is no question that herbicide use in agriculture and particularly in no-till farming systems can be a problem. There is plenty of scientific and practical evidence of excessive herbicide use in no-till farming. However, this is not an inherent characteristic of no-tillage farming, as there are alternative ways for weed management even without returning to soil tillage and cultivation. If correctly applied, these practices allow a sustainable use of herbicides in an integrated weed management programme  and even completely non-chemical weed control is possible. These practices are already successfully applied in commercial farming, but globally they are not yet sufficiently known or appreciated. Therefore, the general perception remains that no-tillage farming requires increased herbicide rates, which in reality not true as a general statement.

(Source – http://www.fao.org/ag/ca/CA-Publications/Pesticide%20Outlook%202005.pdf)

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Erosion: soil at risk

While soil is a resource that can re-create itself, it is a very slow process. Unfortunately, soils have been and continue to be degraded at an alarming rate. Soil erosion is still the dominant cause of soil degradation. Other causes of soil degradation include: soil compaction, soil acidification, soil pollution, and salinization. Dramatic increases in the use of no-till systems by American farmers have led to many benefits, including reductions in erosion, and savings of time, labor, fuel, and machinery. Between 1990 and 2000, no-till farming acreage rose from 16 million acres to 52 million acres, an increase of 300 percent. Now that some fields have been under no-till production systems for many years, farmers and researchers have begun to notice additional. The erosion rate is often greater than the soil formation rate. For instance, the average soil erosion rate in Pennsylvania was 5.1 tons/acre in 1997, whereas the tolerable soil loss level is 3-4 tons /acre per year for most of the soils of this state. With the average loss of 5.1 tons/acre, you can see that the tolerable soil loss level was far exceeded on many fields. That means that our current rate of erosion is a threat to the future productivity of the soil.

Soil erosion removes the best portion of the soil—the part that contains most of the plant nutrients and soil organic matter. In many cases, the topsoil has more favorable soil texture for crop growth than the subsoil. When the topsoil is gone, the farmer is left with less productive subsoil. In addition, eroded soil becomes an environmental threat; polluting streams, lakes, and estuaries. In Pennsylvania, sediment is still the number one pollutant of streams and other bodies of water.


The process of planting, growing and harvesting brings about a certain amount of expected erosion that is considered acceptable to bring a crop to the table. The tolerable soil loss level is called “T” by soil conservationists. The major soil management practice that causes soil erosion is tillage, the process of preparing a field for seeding. Erosion due to tillage can be kept in check through methods such as contour farming, contour stripcropping, conservation buffers, grassed waterways, terraces and diversions to meet soil loss tolerance levels.  You will find that soil can still move within a field––for example, in a strip cropping system where sediment from unprotected soil is trapped by a down-slope strip with high residue or permanent cover. In fact, average soil loss on this entire field or system may be at, or below T, where it exceeds T on the tilled strips. But, if soil can be kept covered, erosion can be stopped before it starts and T can be met on the entire field every year.

The way to dramatically reduce soil erosion is the no-till systems approach. This method keeps the soil covered with crop residue, reduces soil disturbance to almost zero, and attempts to maximize the number of days in the year when living roots grow in the soil.

Farmers and researchers have demonstrated that there are many other benefits to the no-till system besides soil savings. For example, a farmer can save significant amounts of time not working the fields prior to planting. That can result in more timely planting as well as increased acreage that can be managed with the same equipment and labor force. The efficiency of field operations will also increase because the farmer can often meet soil conservation requirements in a no-till system without adding as many conservation practices. Finally, the costs of producing a crop are ,decreased by excluding tillage machinery expenses.

Soil will improve over time in a no-till system through increased organic matter. Soil structure and water infiltration will improve in a no-till system through the slow, but continuous decomposition of crop residue and roots and the high activity of living organisms creating a permanent macro-pore system in the soil. Due to this high biological activity in  no-till, soil compaction can be minimized.Finally, there are other environmental benefits of a no-till system that extend beyond the farm––cleaner air and streams and increased groundwater recharge.

(Source – http://panutrientmgmt.cas.psu.edu/pdf/rp_better_soils_with_noTill.pdf)

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Effective micro-organisms for ecological agriculture during transition

About 25 years ago, I came to know about Effective Microorganisms and their use in agriculture, animal health and sanitation through a Japanese friend who visited my farm and also arranged to get literature about Effective Microorganisms. Prof. Teruo Higa, an agronomist, modified an age-old Japanese technology which he learnt from his grandmother. Traditionally, Japanese farmers used to make ‘Bokashi’, a concentrated form of  compost, apply it to the soil along with other organic manures. The purpose was to inoculate beneficial organisms to improve the quality of organic manure and to check fungus and virus problems in the  soil. They used to collect chemical free soil, rich in humus, from forests and mix it with dry cow dung powder, dry fish meal, jaggery syrup, oil cake and rice bran, adding about 10% to 12% of potable water. The anaerobic compost thus prepared was used at the rate of 100 grams per square metre of land. Prof. Higa, further worked on this traditional practice along with his friend, a microbiologist and introduced Effective Microorganisms to agriculture, animal health and sanitary uses. Now, almost after 30 years of its introduction, it is being used in most of the countries all over the world. In India, through its licensed tie-up with Maple Orgtech (I) Limited, the Effective Microorganisms are being supplied through their distributors all over India.

What is EM?

EM contains more than 70 beneficial organisms, more importantly  lactic acid bacteria, photosynthetic bacteria (Rhodopseudomonas Palustris) and yeast. Surprisingly, use of EM helps in augmenting the photosynthesis by about 30% in all the crops. Further, it controls viruses and fungal damage to crops and animals by inoculating lactic acid bacteria and actinomycetis bacteria. It is very expensive and not very effective to use the stock solution. So, the farmer has to prepare Secondary Effective Microorganisms (SEM) or Extended Effective Microorganisms (EEM).

To prepare SEM/EEM, we need a 20 litre plastic can, free from chemicals, 20 litres of potable water (not chlorinated, or bleaching power being used for purification), 1 or 2 kgs of chemical free Jaggery. Mix jaggery in 20 litres of water in the plastic can and add one litre of Effective Microorganisms stock solution. Close the lid and keep in a cool and dark place for about 8 to 10 days. The PH will come down to 3.5 and the processed product – E.E.M or S.E.M will smell sweet and sour like a mixture of jaggery and curd.

Ways in which EEM can be used

E.E.M or S.E.M can be used in agriculture in 5 ways.

1. Direct use of E.E.M

You can spray E.E.M. directly on crops at 0.1% or one ml in one litre of water. You can also spray on the soil or crop residues at 0.5% to help them break down much faster (particularly sugarcane and paddy thrash). If you have S.E.M in excess, not being used after 60 days, you can spray at 0.5% on your compost heap.

2. Enriched Urine with E.E.M

Collect urine including human urine and process anaerobically for 8 days. Mix 50 ml E.E.M with one litre of urine and 100 gms of jaggery and spray on crops at the rate of one ml in one litre of water. Farmers in Doddaballapura, Bangalore Rural district, Karnataka State area are collecting urine from school latrines and are using on their crops as soil application as they hesitate to spray on crops. But for sure there will be no traces of bad odour after addition of E.E.M and fermentation done anaerobically.

3. Fermented Plant Extraction (F.P.E)

Collect about 10 kgs of weeds at the time of sunrise and cut them into 2 inch pieces. Fill them into a plastic container with water, adding 500ml of E.E.M. and 500 ml of jaggery syrup. Close the lid, not too tight, as this particular fermentation releases some gas. Allow it to ferment for 8 days, in a cool and dark place. You will find clear odourless liquid which can be strained in a cotton cloth. This sap can be sprayed on the crops at one ml in one litre of water i.e., at the rate of 0.1%.

4. Bokashi or concentrated compost

You need 100 litres of fine rice or wheat bran, 10 kgs of dry cow dung powder, 10 kgs of groundnut oil cake, 5 kgs dry fish meal, 2 kgs of jaggery, about 12 to 14 litres of chemical free potable water, one litre of SEM or EEM and a suitable plastic container to fill all the above material. Mix all the ingredients well and fill into the container as tightly as possible for anerobic composting for 8 to 10 days in a cool and dark place. The pH will come down below 3.5 and the product can be mixed with soil at a cooler time along with other organic manures at the rate of 100 gms per square metre.

5. E.M. 5

You will need 600 ml of chemical free potable water, 100 ml of jaggery syrup, 100 ml of E.E.M or S.E.M, 100 ml of ethyl alcohol (rum or brandy) and 100 ml of natural vinegar. Fill and mix all the above ingredients in 1 litre bottle and allow to ferment anerobically in a cool and dark place for 8 to 10 days.

The pH will come down to 3.5. You can spray EM 5 as an antifungal, antiviral and insecticide at the rate of one ml in one litre of water. In my vast experience on my family’s five mixed (bio-intensive) farms, I can recommend the use of EM to increase soil fertility and suppress development of harmful organisms. In the first two to three years, we used EM as a 5 percent spray on our crop residues such as maize, rice paddy stubble and sunflower, to decompose them quickly. We noticed that by using EM spray, composting is quicker and better. Similarly, when we applied bokashi (another EM product) together with farmyard manure, we noticed that our rice, tomato, bottlegourd, soyabean, gladiolus, banana and papaya crops were free from fungal attacks and viral diseases. Another EM preparation was very useful in controlling sucking insects on legumes and cucurbits. We have observed better growth in the leaves and stems of crops sprayed with different EM preparations, leading to yield increases of 15 percent and fewer pest infestations.

Farmers in Erode District of Tamil Nadu in South India, are regularly using EM preparations for soil treatment to check root-rots. Farmers in Raichur District, Karnataka State are using EM to help quicken the breakdown of paddy stubble, as do sugarcane growers in Sivaganga District, Tamil Nadu. The EPPL thermal power company, with 700 acres of hill neem trees (also in Tamil Nadu), found that the germination capacity of their seeds increased from 5 percent at the beginning to 85 percent after soaking their dry fruits in 5 percent EM solution for 24 hours before planting. I myself and over 500 farmers in the area also use EM solution to soak all our seeds before  sowing.

Care in use of EM

Since Effective Microorganisms are basically an inoculum of beneficial organisms, care needs to be taken not to use any chemicals in the same land. Also, as these are acidic in nature, EM preparations of 0.1% only should be sprayed, otherwise, it may scorch the plants. All the preparations have to be stored in a cool and dark place and should be used before 60 to 70 days of preparation.

Although some farmers produce their own micro-organism mixtures, for example, keeping rice gruel near humus rich wet soil for 4-5 days, my fear is that farmers cannot identify any harmful organisms getting into the preparations, as they do not have suitable laboratory equipment to segregate them. Therefore, I think it is better to get EM stock solution from an authentic laboratory. It is very cheap to use it; in India, the use of EM on one acre costs less than a cup of coffee. Farmers use it 3-4 times a year on all their crops. Nevertheless, it is enough to use EM preparations only in the first 2-3 years during the transition from chemical to organic  farming. It is very useful in building up the population of beneficial

organisms both in the soil and plants. In my opinion, use of EM is the best way for farmers intending for a transition from chemical farming to bio-intensive farming.


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Open System for Organic Agriculture Administration

Efforts to increase the availability of sustainable development in natural resources worldwide are  consecutive and proliferated through the last decades. Sectors and divisions of many scientific  networks are working simultaneously in separate schemas or in joined multitudinous projects and  international co-operations. Organic Agriculture, as a later evolution of farming systems, was  derived from trying to overcome the accumulative environmental and socioeconomic problems of  industrialized communities and shows rapid development during the last decades. Its products  day to day gain increased part of consumer preferences while product prices are rather higher  than those of the traditional agriculture. Governments all over the world try to reduce the  environmental effects of the industrialized agriculture, overproduction and environmental  pollution, encouraging those who want to place their fields among others that follow the rules  of organic agriculture. All the above make this new trend very attractive and promising.

But the rules in organic agriculture are very restrictive. The intensive pattern of cultivation  worldwide and the abuse of chemical inputs, affected the environment, therefore any field  expected to be cultivated under the rules of organic agriculture has to follow certain steps but  also be ‘protected’ from the surrounding plots controlling at the same time different kind of unexpected influx (e.g., air contamination from nearby insecticides’ use, water pollution of  irrigation system from an adjacent plot that has used fertilizers, etc). It is obvious that the gap  between wish and theory and the implementation of organic agriculture is enormous.

Obviously one can overcome this gap using a sophisticated complex system. Such a system  can be based on a powerful GIS and the use of widely approved mobile instruments for  precise positioning and wireless communication. In such a system data-flow could be an  “easy” aspect, providing any information needed for the verification of organic product cycle  at any time, any site. 


As the world’s population has increased from 1.6 billion at the beginning of the 20th century  to over 6.2 billion just before the year 2004, economic growth, industrialization and the demand for agricultural products caused a sequence of unfortunate results. This aggregation of disturbances moved along with the reduction in availability and deterioration of maximum yield results from finite ranges of plots on earth’s surface. Overuse of agrochemical products (insecticides, pesticides, fertilizers, etc.), reduction and destruction of natural resources, decrease of biodiversity, reduction of water quality, threat over rare natural landscapes and wild species and an overall environmental degradation, appeared almost daily in news worldwide especially over the last two decades. The universal widespread of this situation has raised worldwide awareness of the need for an environmentally sustainable economic development. (WCED, 1987) In the beginning of year 2004, EU Commission for Agriculture, Rural Development and Fisheries declared three major issues towards a European Action Plan on organic food and farming that may be crucial for the future of organic agriculture:

− the market, (promotion and distribution)

− the role of public support and,

− the standards of organic farming.

It is obvious that in general the market has a positive reaction if there is a prospect of considerable gain. Thus we can say that the other two will define the future. The strict rules of organic agriculture have to be ensured and all the products have to be easily recognisable.Also a guarantee about the quality and the origin of any product has to be established.

Organic Farming is derived as a sophisticated sector of the evolution of farming implementation techniques aiming through restrictions and cultivated strategies to achieve a balanced production process with maximum socioeconomic results (better product prices, availability of surrounding activities as ecotourism, family employment in low populated villages, acknowledge of natures’ and rural environments’ principles and needs, etc.). Meanwhile, the combination of latest technological advances, skills, innovations and the decline of computer and associate software expenses were transforming the market place of geographic data. Now, more than ever before, common people, farmers, private enterprises, local authorities, students, researchers, experts from different scientific fields, and a lot more could become an important asset supporting the development of innovations of Informatics in Geospatial Analysis. With the use of Geographic Information Systems and Internet applications various data can be examined visually on maps and analyzed through geospatial tools and applications of the software packages. Much recent attention and efforts has been focused on developing GIS functionality in the Worldwide Web and governmental or private intranets. The new applicable framework, called WebGIS, is surrounded with a lot of challenges and is developed rapidly changing from day to day the view of contemporary GIS workstations.

Precision Organic Agriculture through GIS fulfils the demands of design strategies and managerial activities in a continuing process. By implementing this combination, certified methods for defining the best policies, monitoring the results and the sustainability of the framework, and generating a constructive dialogue for future improvement on environmental improvement and development could be developed.


Organic Agriculture is derived from other organized smaller natural frameworks, publicly known as ecosystems which are complex, self-adaptive units that evolve through time and natural mechanisms and change in concern with external biogeochemical and natural forces.

Managing ecosystems should have been focused on multiplication of the contemporary needs and future perspectives to ameliorate sustainable development. Instead, political, economic and social agendas and directives, as well as scientific objectives resulted in few decades such an enormous amount of global environmental problems like never before in the history of mankind. Valuable time was spent over the past 75 years by research, which was trying to search how ecosystems regulate themselves, for example how they adjust to atmospheric, geologic, human activities and abuse (Morain, 1999).

Organic Agriculture flourished over the last decade particularly after 1993 where the first act of Regulation 2092/91 of European Union was enforced. Until then, and unfortunately, afterwards, worldwide environmental disasters ( e.g., the Chernobyl accident of the nuclear reactor in April 1986), accumulative environmental pollution and its results (acid rain, ozone’s hole over the Poles, Greenhouse effect, etc.) and even lately the problems that occurred by the use of dioxins and the propagation of the disease of “mad cows”, increase in public opinion the relation between natures’ disturbances and the continuing abuse of intensive methods of several industrialized chains of productions. Among them, conventional agricultural intensive production with the need of heavy machinery, enormous needs of energy consumptions and even larger thirst for agrochemical influxes the last fifty years, created environmental disturbances for the future generations. Therefore, IFOAM (International Federation of Organic Agriculture Movements) constituted a number of principles that, enabling the implementation of Organic Farming’s cultivation methods, techniques and restrictions worldwide.

Principles of Organic Agriculture Organic Agriculture:  (Source: IFOAM)

  •  aims on best soil fertility based in natural processes,
  •  uses biological methods against insects, diseases, weeds,
  • practices crop rotation and co-cultivation of plants
  • uses “closed circle” methods of production where the residues from former cultivations or other recyclable influx from other sources are not thrown away, but they are incorporated, through recycling procedures, back in the cultivation (use of manure, leaves, compost mixtures, etc.),
  • avoids heavy machinery because of soil’s damages and destruction of useful soil’s microorganisms,
  • avoids using chemicals,  avoids using supplemental and biochemical substances in animal nourishing,
  •  needs 3-5 years to transit a conventional cultivated field to a organic farming system following the restrictions of Council Regulation (EEC) No 2092/91,
  • underlies in inspections from authorities approved by the national authorities of Agriculture.

An appropriate organic plot should be considered as the landscape where ecological perspectives and conservations activities should be necessary for effective sustainable nature resource management (Hobs, 1997). Considerable amounts of time and effort has been lost from oncoming organic farmers on finding the best locations for their plots. Spatial restrictions for placing an organic farm require further elaboration of variables that are affecting cultivation or even a unique plant, such as:

− Ground-climatic variables (e.g., ground texture, ph, slope, land fertility, history of former yields, existence of organic matter, rain frequency, water supply, air temperature levels, leachability, etc.),

− Adjacency with other vegetative species (plants, trees, forests) for propagation reasons or non-organic cultivations for better controlling movements through air streams or erosion streams (superficial or in the ground) of agrochemical wastes,

− Availability of organic fertilization source from neighbored agricultural exploitations,

− Quality of accessing road network for agricultural (better monitoring) and marketing (aggregated perspectives of product distribution to nearby or broadened market area) reasons.

A GIS is consisted of computerized tools and applications that are used to organize and display geo-information. Additionally it enables spatial and non-spatial analysis and correlation of geo-objects for alternative management elaborations and decision making procedures. This gives the ability to GIS users or organic farm-managers to conceive and implement alternative strategies in agricultural production and cultivation methodology.


The development of first concepts and ideas of a precision organic farming system in a microregion, demands a regional landscape qualitative and recovery master plan with thorough and comprehensive description of the territory (land-use, emission sources, land cover, microclimatic factors, market needs and other essential variables. Essential components on a successful and prospective organic GIS-based system should be:

− The time-schedule and task specification of the problems and needs assessments that the design-strategy is intended to solve and manage,

− Integrated monitoring of high risks for the cultivation (insects, diseases, water quality, water supply, weather disturbances (wind, temperature, rain, snow, etc.),

− Supply of organic fertilization because additional needs from plants in certain periods of cultivation could be not managed with fast implemented agrochemicals; instead they need natural fermentations and weather conditions to break down elements of additional fertilization,

− High level of communication capabilities with authorized organizations for better management of the cultivation and geodata manipulation, aiming on better promotional and economical results,

− Increased awareness of the sustainability of the surrounding environment (flora and fauna), enabling motivation for a healthy coexistence. For example, the conservation of nearby natural resources such as rare trees, small bushes and small streams, give nest places and water supply capabilities to birds and animals that help organic plants to deal with insect populations controls and monitoring of other plant enemies,

− Continual data capture about land variables, use of satellite images, georeference  sampling proccedures and spatial modelling of existed or former geospatial historical plot’s data could be used to establish a rational model which will enable experts and organic farmers to transform the data into supportive decision applications.

The combination and modeling of all necessary variables through any kind of methodological approach, could be achieved through GIS expressing the geographical sectors of land parcels either as a pattern of vector data, or as a pattern of raster data (Kalabokidis et al., 2000). Additionally, we could allocate the cultivation or the combination of cultivations1 and their units (plants, trees, etc.) so as to be confronted in relation with their location inside the field, as well as with the neighbored landscape. For this purpose the most essential tool would be a GPS (Global Positioning System) device with high standards of accuracy. Several statistical approaches and extensions have been developed for the elaboration of spatial variables through geostatistical analysis. The usefulness of these thematic maps lies upon the tracing and localization of spatial variability in the plot during the cultivated period, enabling the farmer to implement the proper interferences for better management and future orientation of the farm and of the surrounding area.

Specific geodata receivers and sensors inside the plot, in the neighbored area, as well as images from satellites, could establish a “temporal umbrella” of data sources of our farm which would submit in tracing of temporal variability factors in our field. The agricultural management framework that takes into account the spatial or temporal variability of different parameters in the farm is called Precision Agriculture (Karydas, et al., 2002). The implementation of IFOAM’s principles in such an agricultural model should be called Precision Organic Agriculture (POA).


The development of appropriate analytical techniques and models in a variety of rapidly changing fields using as cutting edge GIS technology, is a high-demanding procedure. The linkages to different applications of spatial analysis and research and the ability to promote functional and integrated geodatabases is a time consuming, well prepared and carefully executed procedure which combines spatial analytic approaches from different scientific angles: geostatistics, spatial statistics, time-space modeling, mathematics, visualization techniques, remote sensing, mathematics, geocomputational algorithms and software, social, physical and environmental sciences.

An approach of a Precision Organic Farming model, which uses as a structure basis the Precision Agriculture wheel (McBratney et al., 1999) and the introduction of organic practices for the sustainable development with the elaboration of any historical data about the plot. The basic components are:

− Spatial referencing: Gathering data on the pattern of variation in crop and soil parameters across a field. This requires an accurate knowledge of allocation of samples and the GPS network.

− Crop & soil monitoring: Influential factors effecting crop yield, must be monitored at a thoroughly. Measuring soil factors such as electric conductivity, pH etc., with sensors enabling real-time analysis in the field is under research worldwide with focusing on automation of results. Aerial or satellite photography in conjunction with crop scouting is becoming more available nowadays and helps greatly for maximizing data acquisition for the crop.

− Spatial prediction & mapping: The production of a map with thematic layers of variation in soil, crop or disease factors that represents an entire field it is necessary to estimate values for unsampled locations.

− Decision support: The degree of spatial variability found in a field with integrated data elaboration and quality of geodata inputs will determine, whether unique treatment is warranted in certain parts. Correlation analysis or other statistical approaches can be used to formulate agronomically suitable treatment strategies.

− Differential action: To deal with spatial variability, operations such as use of organic-“friendly”-fertilizers, water application, sowing rate, insect control with biological practices, etc. may be varied in real-time across a field. A treatment map can be constructed to guide rate control mechanisms in the field.

GIS systems from their beginning about than 30 years ago, step by step, started to progress from small applications of private companies’ needs to high demanding governmental applications. At the beginning, the significance and capabilities of GIS were focusing on digitizing data; today, we’ve reached the last period of GIS’s evolution of data sharing. Nowadays restrictions and difficulties are not upon the hardware constraints but they are on data dissemination. Several initiatives have been undertaken in order to provide basic standard protocols for overcoming these problem. The need of organisational and institutional cooperation and establishment of international agreement framework becomes even more important. Governments, scientific laboratories, local authorities, Non Governmental Organizations (NGOs), private companies, international organizations, scientific societies and other scientific communities need to find substantial effort to broaden their horizons through horizontal or vertical standards of cooperation.

Any GIS laboratory specialized in monitoring a specific field could give additional knowledge to a coherent laboratory which focus to an other field in the same area. As a result, especially in governmental level, each agency performs its own analysis on its own areas, and with minimal effort cross-agency interactions could increase the efficiency of projects that help the framework of the society.

Such a data-sharing framework was not capable in earlier years, where technological evolution was trying specific restrictions of earlier operational computerised disabilities. Hardly managed and high demanding knowledge in programming applications, unfriendly scheme of computer operating systems over large and expensive programs, and restricted knowledge on Internet applications now belong to the past. User friendly computer operation systems, high storage capacity, fast CPUs (Central Processing Units) sound overwhelming even in relation with PCs before ten years. Powerful notebooks, flexible and strong PDAs, super-computers of enormous capabilities in data storage, true-colour high resolution monitors and other supplementary portable or stable devices, created an outburst in the applications of Information Technology (IT). Additionally, the expansion of Internet in the ‘90s worldwide, contributed (and is still keeping on doing this) on redesigning specific applications for data mining procedures through WWW (World Wide Web), as well as for data exporting capabilities and maps distribution through Internet. The evolution in computer software derived new versions of even friendlier GIS packages.


The Internet as a system followed an explosive development during the past decade. The modern Internet functions are based on three principles (Castells, 2001):

 − Decentralized network structure where there is no single basic core that controls the whole system.

− Distributed computing power throughout many nodes of the network.

− Redundancy of control keys, functions and applications of the network to minimize risk of disruption during the service.

Internet is a network that connects local or regional computer networks (LAN or RAN) by using a set of communication protocols called TCP/IP (Transmission Control Protocol/Internet Protocol). Internet technology enables its users to get fast and easy access to a variety of resources and services, software, data archives, library catalogs, bulletin boards, directory services, etc. Among the most popular functions of the Internet is the World Wide Web (WWW). World Wide Web is very easy to navigate by using software called browser, which searches through internet to retrieve files, images, documents or other available data.

The important issue here is that the user does not need to know any software language but all it needs is a simple “click” with mouse over highlighted features called Hyperlinks, giving  increased expansion on growth of WWW globally.

GIS data related files (Remote Sensing data, GPS data, etc) can benefit from globalization of World Wide Web:

− An enormous amount of these data are already in PC-format.

− GIS users are already familiar by using software menus.

− Large files could be easily transmitted through Internet and FTPs and software about compression.

− The Web offers user interaction, so that a distant user can access, manipulate, and display geographic databases from a GIS server computer.

− It enables tutorials modules and access on educational articles.

− It enables access on latest achievements in research of GIS through on-line proceedings of seminars, conferences, etc.

− Through Open Source GIS, it enables latest implementations of GIS programming and data sharing by minimum cost.

− Finally through online viewers, it gives the capability of someone with minimum  knowledge on GIS to get geospatial information by imaging display. (Aber, 2003)

The importance of World Wide Web could become more crucial through wireless Internet access. For a GIS user who works on the street, or in our case, on the field of an organic farm and uses wireless access to the web, a GIS package through a portable device, data transmission is an important issue. This is more important especially if the data are temporalaffected (e.g., meteorological data). To overcome this problem, new data transmission methods need to be elaborated and used in web-based GIS systems to efficiently transmit spatial and temporal data and make them available over the web. Open Source GIS through Internet represents a cross-platform development environment for building spatially enabled functions through Internet applications. Combinations of freely available software through WWW (e.g., image creation, raster to vector, coordinates conversion, etc), with a  combination of programming tools available for development of GIS-based applications could provide standardized geodata access and analytical geostatistical tools with great diplay efficiency. Under this framework, several geospatial applications can be developed using existing spatial data that are available through regional initiatives without costing anything to the end user of this Open GIS System (Chakrabarti et al., 1999).


As the World Wide Web grew rapidly, sophisticated and specialized methods for seeking and organizing data information have been developed. Powerful search engines can be searched by key words or text phrases. New searching strategies are under development where web links are analyzed in combination with key words or phrases. This improves the effectiveness at seeking out authoritative sources on particular subjects. (Chakrabarti et al., 1999) Digital certification under international cooperatives and standards is fundamental for the development of organic agriculture in general and particularly in the market framework. Based on the theory of “dot per plot” different functional IDs could be created under password protected properties through algorithm modules. This way, a code bar (like those on products in supermarkets) could be related through GIS by farmers ID, locations ID, product ID, parcel ID and could follow this product from organic plot to market places giving all the details about it. Even more, authorization ID could be established this way for controlling even the farmer for cultivated methods undertaken in the field that are underlie EUs’ legislations and directives.

 In many cases the only way to create or maintain a separate “organic market” is through certification which provides several benefits (Raghavan, et al., 2002):

− Production planning is facilitated through indispensable documentation, schedules, cultivation methods and their development, data acquisition (e.g., lab results on soil’s pH, electrical conductivity, organic conciseness, etc.) and general production planning of the farm − Facilitation of marketing, extension and GIS analysis, while the data collected in the process of certification can be very useful as feedback, either for market planning, or for extension, research and further geospatial analysis.

− Certification can facilitate the introduction of special support schemes and management scenarios for organic agriculture, since it defines a group of producers to support.

− Certification tickets on products under international standards improve the image of organic agriculture in the society as a whole and increases the creditability of the organic movement.

Because a certification ticket is not recognised as a guarantee standard by itself, the level of control system in biological farming is quite low. In Greece, we are familiar with farmers having a bench by the road and using hand made tickets for their products, they call them “biologic” aiming in higher prices. Marketing opportunities for real organic farmers are eliminating while at the same time EU is trying to organize the directives for future expansion of organic agriculture.

Designing a functional infrastructure of a Geodatabase, fully related with Internet applications, requires accumulative levels of modular mainframes that could be imported, managed and distributed through WWW applications. The security and reliability of main GIS databases have to be established and confirmed through international standards (ISOs) and authorized GIS packages and users as well as in relation with governmental agencies. On the next level, additional analysis of geodata files and agricultural related information data should be combined and further elaborated. For the base level, fundamental GIS functions and geodata digitization should be implemented through internetic report applications (HTML reports, site-enabled GIS, wireless GIS applications, etc.). By this framework we could create a data base where using any ID number (farmer, product, field, etc) will be easy to recognize the history of any specific item involved in the life cycle of the organic farming through a data-related link over thematic maps by GIS viewers in the Internet. Although this framework is supported by multifunctional operations, we could distinguish sectors with homogeneity features:

In the first level of accessing an Open GIS Web system, the users should be first able to access the system through a Web browser. Free access should be available here for users who want to retrieve information, as well for users who want to login for further, more advanced queries. Fundamental GIS functions and geodata digitization should be implemented through internetic report applications (HTML reports, site-enabled GIS, wireless GIS applications, etc.). In this level public participation is enabled through importing additional geodata sets and any other kind of information resources (for example, latest weather information, market demands, research accomplishments, latest equipment facilities, personal extensions for GIS packages, etc.). The eligibility of these data should be applied after studying standards criteria in the next level by experts. Technological advances are also providing the tools needed to disseminate real-time data from their source to the web mapping services, available to the users through the Internet, portable devices, cellular telephones, etc. Basic field work for agricultural and Remote Sensing purposes, as well as data gathering for further statistical analysis should be implemented. By this level, the user could access the system through browsing commands or hyperlinks and through GIS queries. The significant point here is that the access is completely free for anyone who wants to retrieve information but classified to everyone who wants to submit any kind of information by the meaning that he has to give either a user’s ID or personal details.

The second level of accessing the system , is the authorized expert’s level. Here additional analysis of geodata files and agricultural related information data should be combined and further elaborated. Expert analysts from different scientific fields (GIS, economists, topographers, agriculturists, ecologists, biologists, research, etc.) are “bridging” the two levels of the system by using high sophisticated computer tools and GIS packages to facilitate data transportation through WWW channels between clients and servers. In the database file an identity code (IdC) or feature code (FC) is distributed, following the geodata file from main Geodatabase server to the final user. By this framework we could create a data base where using any ID number (farmer, product, field, etc) will be easy to recognize the history of any specific item involved in the life cycle of the organic farming through a data-related link over thematic maps by GIS viewers in the Internet. Additional demand on this level should be considered to be indispensable a background in Web functions with further support by Web experts for adequate Web System Administration.

In the third level of this Web based GIS system,  the success is relying on cooperation between authorized users only. This partnership should be established between geographic information data providers and data management authorities at a governmental, local or private level by authorized personnel. International collaboration could provide even better results in data quality and quantity but requires additional data storage capabilities and special awareness on data interoperability and standards interchange eligibility confirmed through international standards (ISOs). The security of personal details must be followed enriching this level with further authorization controlling tools. The significance of designing successful strategies for case management, using authorized, legitimate GIS packages should also be supported through Web applications and algorithms available for GIS-Web users on global based patterns .


The generally accepted purpose of organic agriculture is to meet the needs of the population and environment of the present while leaving equal or better opportunities for those of the future. Development of this sector is increasing through coordinated activities worldwide by international organizations (EU, UN, FAO, etc.) with long-lasting master plans. The dynamic factor of organic agriculture should not be kept without support. Political initiatives should stand side by side with organic farmers helping them to increase the quality of products and to multiply the number of producers and of the cultivated area.

The accumulative development of Organic Agriculture in Europe needs to be followed by additional development of management activities and strategies in national, binational and international level. Combined actions should be undertaken in fields like telecommunications standards, computer software and hardware development, research projects on agricultural management through GIS, additional educative sectors in universities.

The restrictions that accompany organic farming should help in establishing international agreements that will help to increase the number of qualitative standards, allowing better perspectives for developing future GIS based management strategies. The implementation of an Internet Based Precision Organic Agricultural System requires committed research from the agricultural industry and improvements in geoanalysis, agricultural and information technology. GIS based systems will become more essential as a tool to monitor agricultural exchanges between inputs and outputs and in relation with adjacent regions at an increasingly detailed level. The results will enhance the role of Geographic Information as a functional and economic necessity for any productive community.

(Source – http://www.fig.net/pub/athens/papers/ts20/ts20_5_ifadis_et_al.pdf)

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Precision farming is a method of crop management by which  areas of land within a field may be managed with different levels of input depending upon the yield potential of the crop in  that particular area of land. The benefits of so doing are two  fold:

− the cost of producing the crop in that area can be  reduced;

− the risk of environmental pollution from  agrochemicals applied at levels greater than those required by the crop can be reduced.

Precision farming is an integrated agricultural management  system incorporating several technologies. The technological  tools often include the global positioning system GPS,  geographical information system GIS, remote sensing, yield  monitor and variable rate technology.

The paper talks about the use of GPS to support agricultural  vehicle guidance. Equipment for this purpose consists on a  yield monitor installed: the system supports human guide by  means of a display mapping with a GIS the exact direction  produced by GPS receiver put on vehicle top: the driver  follows it to cover in an optimal path the full field.

GPS receivers for this applications require, not only an high accuracy to ensure the reduction of input products, but even an  easy and immediate way of use for farmers; without forgetting low costs. Obviously the technology to achieve high precision still exists but it is too expensive and difficult to use for not skilled people. Survey modality usually adopted in agricultural applications is real time kinematic positioning, DGPS RTK, which enable tohave a good accuracy by means of corrections received. In this experimentation the aim is to obtain a sub-metric accuracy using low cost receivers, which can provide only point positioning. These receivers have been developed for maritime navigation purposes; our aim is their optimization in order to apply them for land navigation in particular for farming activities. Some tests using these receivers were carried out, but results were not satisfying and probably the reason has to be assigned to the implementation of a Kalman filtering inside the receiver software. This is the starting point for a new project, at the moment still in progress, which aim to develop a new  algorithm based on Kalman filter. Its purpose is to improve low cost receiver outputs in order to optimize trajectories and to reach needed accuracy in vehicle positioning during agricultural  activities.


1 Instruments and tests

Experimentation has been carried out using Leica Geosystems  instruments; in particular the low cost receiver discussed in the paper is the TruRover Leica. Its mainly features are: it is an antenna-receiver integrated instrument, it has a 5 Hz tracking time, the report is in the NMEA string format, it cannot neither store positions nor show them in real time, it requires a computer to view NMEA data stream. TruRover performances were compared with geodetic receiver one, which are considerably better, so they are the perfect comparison condition to estimate Trurover positioning quality.

Geodetic receiver used is the GX1230 Leica, able to receive double frequency (both code and phase). Both static and kinematic tests were performed, simulating the typical behaviour of an agricultural vehicle (straight and parallel trajectories with reduced velocity, such as 20÷40 km/h)

and using, at the same time, the two different kinds of GPS receivers described above. At the top of the vehicle, both TruRover and geodetic antenna, connected to the receiver, were placed at a distance of 50 cm. Three static stops with 20 minutes time length were performed, spaced with two steps in motion. Geodetic receiver were set with a 1 second tracking time and a cut off angle of 10 degree. Tests length were about two hours. Another geodetic receiver were placed for a single point positioning and used as the Master station for the following data processing.

2. Data processing

Master station coordinates were determined by means of a static processing in relation to two different GPS permanent station in order to check result: one placed in Modena, where tests have

been carried out, led by INGV and the other located near Bologna, led by ASI Telespazio.

TruRover NMEA data already contain coordinates and Visual GPS software has been utilized to show and store them. These positions have been compared to data stored by double frequency receiver during kinematic tests. These data were utilized to estimate the exact trajectory, which was estimated by the postprocessing in kinematic differential modality. Software for data processing was Leica Geo Office. To be honest this trajectory is not exact because even kinematic postprocessing data have some errors; however this modality has a centimetric accuracy, better than the required from agricultural applications one so it is not a mistake to consider this track as an exact one. TruRover track and the exact one are not yet comparable because 50 cm shift still exists: a kind of overlap has been done by means of setting vehicle motion direction thanks to postprocessed trajectory.

3 Results analysis

The results of the comparison between TruRover track and double frequency receiver one are not satisfying; indeed receivers utilized in experiments show some problems in curves, where the estimated track is larger than the exact one. This bad performance may be due to the presence of a Kalman filter inside the system, that is not optimized for the specific application. Probably at each epoch this filter uses previous estimated positions in order to anticipate the future one on a constant velocity, linear trajectory assumption. In that way when vehicle curves the filter understand it as a mistake and modify the position; this behaviour causes a delay in curving and consequently a shift in positioning.

Higher precision for agricultural applications is not required in curves but in straight directions, where farmers make their main activities on yield. However curves have a great importance mainly at their end because there it is necessary for the vehicle trajectory to be parallel to the previous one. The main reason for that is to economize input products spread about field. Kinematic trajectory is considered the exact one, the reference for a comparison between pseudo-range and kinematic tracks.

The results show distances greater than 1 meter (the target aimed) but always inside the method precision (10 meters). Statistical parameters, as means and standard deviations,  confirm the same things. Table 2 and 3 relate these statistical  valuers. At the beginning the idea was that Kalman filter needs a period of assessment time to work better; on the contrary,  with the elapsed time the differences increase with a worrying time drift. 



The reason for problems in curve is probably the presence of a Kalman filtering inside TruRover, not especially studied for farming applications. Thereof the need of trying a kind of TruRover performances improvement pursued by means of the development and the implementation of a new algorithm based on Kalman filtering and, at the same time, optimized for agricultural requirements.

The first problem was the choice of the process modelling to put in Kalman equations. In particular two trials have been done and described in the following: the constant velocity model and the constant acceleration model. Before the models description, it will be shortly illustrated Kalman filter principles.


The above described problems are a great problem for precision  farming because bad tracks in the field cause wastes of material, without considering economical and environmental impacts. So that, starting from the analyses of the previous results and taking into account the typical user requirements, a preliminary design for the new algorithm based on Kalman filtering has been done. The idea underlying the new navigation system is to implement a simplified version of the so called adaptive Kalman filtering; the filter takes into account both the typical behaviour of an agricultural vehicle and the a priori knowledge of the planned track and works continuously testing alternate hypotheses in predicting the track. The new Kalman algorithm should both eliminate drifts in curves and occasional spikes in satellite configuration changes. This research project is still in progress; at the moment we have implemented the new algorithm which consists on a double filtering using the constant velocity model in straight trajectories and the constant acceleration model for curve tracks.

Problems during algorithm testing were mainly the lack of raw data, in fact TruRover NMEA reports are still filtered and there is not the possibility to remove the previous filter implemented inside the receiver and it is not mathematically correct utilizing them for another filtering. For

this reason data inputs for new algorithm have been provided from double frequency receiver without post-processing (raw data really as they have been stored). Results confirm the importance to adopt a model based on acceleration in curve, but at the same time it is necessary looking at these results in a critical way because they are outputs originated from inputs  better than Trurover data. In the tests the attention will be mainly focused on variables which have a great importance in the model and parameters choice, such as process covariance and measurement noise. Next steps will be two-fold:

− trying to vary covariance weighs both in system noise matrix and in measurement noise matrix;

− test double filtering with raw data not yet filtered and tracked by a low cost and single frequency receiver, showing located spikes.

The purpose to improve TruRover performances and to optimize them for precision farming is challenging, especially having at our disposal only raw data. Other possible solutions are:

− connecting an odometer and a steering wheel to the system, integrated with the GPS receiver, which supports human vehicle guide. It could be the input to choose, at the right time, the best process model to adopt inside Kalman filter (constant velocity or constant acceleration model).

− utilizing differential positioning, DGPS, improving coordinates thanks to corrections received from a Master station close to the field.

(Source – http://www.isprs.org/proceedings/XXXVI/5-C55/papers/biagi_ludovico_1.pdf)

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Prediction of Moisture Content of Potash Fertilizer Using NIR Spectroscopy

Potash fertilizer supplies the essential element, potassium, for the stimulation of plant growth. It plays a critical role in the growth process and is essential to boost yields of many major crops. Potash fertilizer are available in different types with different physical and chemical characteristics. Potash fertilizer includes red granular, red standard, white granular, white soluble, and pink standard. These products range in size from a fine powder (size ~ 0.2 mm), standard (size ~ 0.8 mm), granular (size ~ 2.5 mm), and coarse with size of almost 4 mm (Garret 1996).

Potash fertilizer is hygroscopic. Fertilizer  adsorbs water when it is exposed to an atmosphere with high relative humidity. If the moisture content of the potash fertilizer exceeds 0.2%, caking and dust formation can occur after subsequent drying (Zhou 2000). Caking and dust formation are problematic because they impede the flow of potash during distribution and agricultural application (Peng et al. 1999).

Knowledge of moisture content in stored potash is crucial because it can be used as a product quality indicator and management tool for potash during its storage, shipment, and handling. Typically, moisture content of potash fertilizer is determined by drying and weighing techniques. Reflectance measurements may represent a suitable alternative. No studies using NIR spectroscopy for determining moisture content of inorganic fertilizers have been undertaken, previously.

Use of NIRS techniques to sense moisture content has been the subject of many other investigations. NIR spectroscopy has been used to measure moisture content of food products, agricultural products, and manure. Ren and Chen (1997) used NIRS to determine the moisture content of ginseng roots. Calibration equations were developed using wavelengths in the 1100 –2500 nm region and first order derivatives and scatter correction were used. High correlation and low SEP were attained during validation.

Near infrared reflectance spectroscopy has also been used to successfully measure moisture content of food products. Pioneering work in this field was conducted by Ben-Gera and Norris (1968a) who used NIRS to measure the near-infrared absorbance properties of meat emulsions. The difference in optical density between 1800 and 1725 nm gave a high correlation to moisture content. Ben-Gera and Norris (1968b) also used NIRS to determine moisture content of ground soybeans. In this research a calibration between moisture content and intensity of the 1940 nm water absorption band was constructed. Adamopoulos and Goula (2004) used NIRS to measure the moisture content of taramoslata, a traditional Greek food. Calibration models based upon six wavelengths were developed using multiple linear regression. Lee et al. (1997) used NIRS to measure moisture content of Cheddar cheese curds. A high degree of correlation was obtained during validation. Wold and Isaksson (1997) used NIRS to determine the moisture content of whole Atlantic salmon, wherein results
showed that NIRS was suitable for non-destructive determination of moisture content.

Finally, NIRS has been used by several researchers to measure the moisture content in manure from several species. Reeves (2001) used NIRS to determine the moisture content of poultry manure. In this research, partial least squares regression (PLS) was used to develop calibration models and spectral data were treated using either multiplicative scatter correction or mean and variance scaling. Malley et al. (2002) used NIRS to determine the moisture content of hog manure in pits and lagoons, with good results. Models were developed using multiple linear regression and first and second order derivatives were used for data smoothing.

The goal of this research was to investigate the correlation between moisture content and spectral reflectance for red standard potash with moisture content between 0 and 1%. This could lead to the development of an ability to remotely sense moisture content in potash piles. Specific objectives were:

1. To investigate reflectance properties of red standard potash in the visible and near infrared portions of the
electromagnetic spectrum, and

2. To select optimum wavelengths and develop models for moisture content prediction based on these wavelengths. <based on>

(Source: Faraji, H., Crowe, T., Besant, R., Sokhansanj, S. and Wood, H., Department of Agricultural and Bioresource Engineering,  Department of Mechanical Engineering, and Department of Electrical Engineering, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. (http://www.engr.usask.ca/societies/csae/protectedpapers/c0301.pdf)

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Potential Long-Term Benefits of No-Tillage and Organic Cropping Systems

There have been few comparisons of the performance of no-tillage cropping systems vs. organic farming systems, particularly on erodible, droughty soils where reduced-tillage systems are recommended. In particular, there is skepticism whether organic farming can improve soils as well as conventional no-tillage systems because of the requirement for tillage associated with many organic farming operations. A 9-yr comparison of selected minimum-tillage strategies for grain production of corn (Zea mays L.), soybean [Glycine max (L.) Merr.], and wheat (Triticum aestivum L.) was conducted on a sloping, droughty site in Beltsville, MD, from 1994 to 2002. Four systems were compared: (i) a standard mid-Atlantic no-tillage system (NT) with recommended herbicide and N inputs, (ii) a cover cropbased no-tillage system (CC) including hairy vetch (Vicia villosa Roth) before corn, and rye (Secale cereale L.) before soybean, with reduced herbicide and N inputs, (iii) a no-tillage crownvetch (Coronilla varia L.) living mulch system (CV) with recommended herbicide and N inputs, and (iv) a chisel-plow based organic system (OR) with cover crops and manure for nutrients and postplanting cultivation for weed control. After 9 yr, competition with corn by weeds in OR and by the crownvetch living mulch in CV was unacceptable, particularly in dry years. On average, corn yields were 28 and 12% lower in OR and CV, respectively, than in the standard NT, whereas corn yields in CC and NT were similar. Despite the use of tillage, soil combustible C and N concentrations were higher at all depth intervals to 30 cm in OR compared with that in all other systems. A uniformity trial was conducted from 2003 to 2005 with corn grown according to the NT system on all plots. Yield of corn grown on plots with a 9-yr history of OR and CV were 18 and 19% higher, respectively, than those with a history of NT whereas there was no difference between corn yield of plots with a history of NT and CC.

Three tests of N availability (corn yield loss in subplots with no N applied in 2003–2005, presidedress soil nitrate test, and corn ear leaf N) all confirmed that there was more N available to corn in OR and CV than in NT. These results suggest that OR can provide greater long-term soil benefits than conventional NT, despite the use of tillage in OR. However, these benefits may not be realized because of difficulty controlling weeds in OR.

No-tillage cropping systems have been shown to offer many benefits to soils and production of grain crops in the eastern USA (Grandy et al., 2006). After 28 yr of continuous tillage treatments in Ohio, the notillage system had higher organic C, cation-exchange capacity, hydraulic conductivity, aggregate diameter, and water-holding capacity than tillage systems (Mahboubi et al., 1993). On well-drained soils, corn and soybean yields were consistently higher with continuous no-tillage than conventional tillage (Dick et al., 1991). No-tillage systems were shown to reduce drought stress and increase yields of grain crops on upland soils in the piedmont of the southern states (Denton and Wagger, 1992). Corn root length density was higher in the top 0.1 m of soil under no-tillage than under conventional tillage, probably a result of higher water-holding capacity, capillary space, and proportion of water-stable aggregates in the surface soil (Ball-Coelho et al., 1998).

Many of the improvements to soils as a result of notillage production are related to increases in soil organic C which in turn relates to improvements in soil aggregation, water-holding capacity, and nutrient cycling (Weil and Magdoff, 2004; Grandy et al., 2006). Soil organic C can also be increased by other strategies, including addition of winter annual cover crops into rotations, diversifying rotations with perennial crops, addition of manure-based amendments, and organic farming, which often employs all of the preceding strategies. For example, soil organic C and N were increased by both reducing tillage and using winter annual cover crops, leading the authors to suggest that the best management system would include no-tillage and a mixture of legume and nonlegume winter annual cover crops (Sainju et al., 2002). Rotations that included at least 3 yr of perennial forage crops had the highest soil quality scores with total organic C being identified as the most sensitive quality indicator (Karlen et al., 2006). Manure- and legumebased organic farming systems from nine long-term experiments across the USA were shown to increase soil organic C and total N compared with conventional systems (Marriott and Wander, 2006). Crop yields and/or soil organic C was increased by organic vs. conventional cropping systems in the East (Pimentel et al., 2005), Midwest (Delate and Cambardella, 2004), and West (Clark et al., 1998).

Most comparisons of soil improvements in organic vs. conventional cropping systems have been conducted under conventional tillage conditions. The dilemma for organic farmers is that the approaches for increasing soil organic C usually require tillage. Specifically, tillage is required for eliminating perennial legumes before rotation to annual crops, for incorporating manure to avoid N volatilization losses, or for preparing a seedbed and controlling weeds. Since an increase in tillage intensity and frequency has been shown to decrease soil C and N (Franzluebbers et al., 1999; Grandy et al., 2006), increases in organic matter by utilization of organic materials in organic farming may be offset by decreases in organic matter from tillage. Some authors have speculated that conventional no-tillage agriculture may provide superior soil improvement and potential environmental benefits compared with organic farming because of the tillage requirement of organic farming (Trewavas, 2004). The need for long-term research has been advocated to assess the relative merits of conventional no-tillage agriculture compared with organic farming (Macilwain, 2004). There is little literature reporting such long-term comparisons. One 6-yr study in Pennsylvania showed that some form of primary tillage was required for crop yields in organic systems to match those in conventional systems, but that a pure no-tillage organic system was not viable (Drinkwater et al., 2000).

A long-term experiment, the Sustainable Agriculture Demonstration Project (SADP), was initiated at Beltsville, MD, to compare selected no-tillage grain cropping systems and a reduced-tillage organic system on a sloping, droughty site typical of the mid-Atlantic piedmont. The standard for comparison was a notillage system typical of that used in this area. Two additional no-tillage systems, one including winter annual cover crops and another including a perennial crownvetch living mulch, were compared with this standard for their potential to improve soil organic matter, reduce external inputs, and enhance environmental protection on erodible soils. Finally, an organic cropping system that reduced tillage to the minimum necessary for incorporation of manure and for weed control was included in this comparison. Performance of these systems during the first 4 yr of the experiment, which included transition years for the organic system, was reported by Teasdale et al. (2000). A simulation of projected yields, economic returns, and environmental impacts was reported by Watkins et al. (2002). This paper reports results from a comparison of these systems over a 9-yr period as well as a 3-yr uniformity trial that followed… <more>

(Source:  John R. Teasdale,* Charles B. Coffman, and Ruth W. Mangum, Agronomy journal-   http://naldc.nal.usda.gov/download/13149/PDF)

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Crop Rotation on Vegetable Farms

Crop rotation is one of the most effective tools for managing pests and maintaining soil fertility, but there aren’t many specific recommendations for how to go about it. A common approach on vegetable farms is to rotate crops by families. Another strategy is to alternate vegetable crops with field or forage crops, such as small grains, alfalfa or clovers. Some growers try to rotate fields so they are in cash crops one year and cover crops the next year. On farms with limited land for rotation out of cash crops, sweet corn is a good crop to rotate with since it hosts very few insects or diseases that affect other vegetables.

Too many growers rotate their crops using the ‘seat of their pants’ technique, relying on memory and making decisions day by day when planting. To make the most of crop rotation you need detailed records of where crops were grown in the past as well as a written plan for how crops will be arranged in the future. Start by making a map of your farm and other fields you may use such as rented fields. Label the fields or sub-fields with names and acreage. Make photocopies of the map and at the end of each season fill one in and date it, noting any serious pest or soil problems in a field. Prior to the growing season, fill in a new map with your best guess as to where crops will go, depending on growing conditions, etc. Try to develop a plan that results in the most years possible between planting similar crops in a given location. As you plan, remember that rotation helps prevent some pests but not others. For insects that over-winter near the crop they infested, such as Colorado potato beetle, European corn borer, or flea beetle, it helps to plant host crops as far away as possible the next year.

Having a barrier such as a road or river between last year’s crop and this year’s can enhance the rotation effect. Rotation will not help prevent insect damage from pests that migrate into the area, such as potato leafhopper or corn earworm. For diseases that are soil-borne or over-winter in crop residues, rotating out of susceptible crops is a key to preventing infection, as in the case of Phytophthora blight, early blight, and many other diseases. However, host crops must be rotated far enough away to avoid infection through blowing or washing soil.

Equipment that moves soil from field to field can also reduce the benefit of rotation. For some diseases, such as clubroot of crucifers, susceptible weed hosts must be controlled if rotation is to be effective. As with insects, rotation cannot prevent airborne diseases that move in from other areas, such as downy mildew, nor can it prevent seed-borne diseases.

In addition to minimizing some pest pressure, rotating crops is also good for soil health because it leads to changes in tillage, rooting depth and nutrient removal. Rotation is also a way to maintain soil organic matter if plans include soil-improving cover crops, a practice that is critical to sustaining productivity over time. Always include winter cover crops in your rotation plans to minimize erosion and add some organic matter back to the soil. Whenever possible, also use summer cover crops for warm-season biomass production and weed suppression. In addition, to the extent possible, one should include one or two year-long green manure crops to ‘rest’ fields  from tillage for substantial periods of time while allowing extensive cover crop root growth to occur… <more>

(Source: Vern Grubinger, Vegetable and Berry Specialist, University of Vermont Extension –  http://www.uvm.edu/vtvegandberry/factsheets/Crop%20Rotation.pdf )

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