eChapters

A treatment is the combination of N & P

If levels of N & P are 5 & 10 respectively, so number of treatments are 5x10=50.

Completely Randomized Design (CRD)

The simplest design using the two essential principles of replication and randomization is the CRD. Suppose that we have t treatments (or t levels of a factor) under comparison and ith treatment is to be replicated r times, for i = 1,2, … t . A particular case of this is equal replication for different treatments, where r1=r2= =r6=r, so that n=rt.

Experimental unit : An experimental unit is the material to which is applied the treatment and on which the variable under study is measured. In an agricultural field experiment, the plot of land, not the individual plant, will be the experimental unit; in a feeding experiment of cows,the whole cow is the experimental unit; in human experiments in which the treatment affects the individual, the individual will be the experimental unit.

Treatment : The different procedures under comparison in an experiment are the different treatments, i.e in an agricultural experiment, the different varieties of a crop or the different manures will be the treatments. In a dietary or medical experiment, the different diets or medicines, etc. are the treatments.

The experimental design and analysis discussed in previous chapters refer essentially to experiments on annual crops. Even when these experiments are repeated in different years, this is done at a new site each year .The use of new crop production practices will generally change the important physical and biological factors of the environment. This process of change can take many years. Generally, the productivity of some types of technology must be evaluated by a series of trials repeated over time. Such trials are generally referred to as long-term experiments. Long-term experiments are those which are continued on the same set of plots over a series of years with a pre-planned sequence of treatments or crops or both. Treatments may be applied every year or periodically. The same crop may be repeated year after year or once planted may continue for several years as perennial trees ,or a sequence of crops may be grown in rotation as for instance rice-rice or rice-wheat (1 year sequence with 2 crops per year ) or sorghum,groundnut,cotton and wheat, each crop cycle being completed in four years. The main features of long-term experiments are as follows :

This is an extension of the analysis of variance to cover the case where observations are taken on more than one variable from each experimental unit. Interest, however, centres on one of these (y, called the dependent variable) and the question is whether the variation of the dependent variable over the classes is due to class effects or due to its dependence on the other variables, (x’s, called the independent or concomitant variables ), which also vary from class to class. The analysis of covariance controls the experimental error by taking ito consideration the dependence of y on x.

In many experimental situations, it becomes necessary to repeat an experiment over time ( for a number of seasons or years ) and / or over space ( a number of places). This repetition ( or replication ) of the experiment broadens the scope of the experiment in the sense that our recommendations will be applicable for a number of seasons /or a number of places . A single experiment performed in one place for only one season will provide recommendations for that place and for that season . It may not be applicable to other places or for other seasons . In the case of agricultural experiments , for example , there may be present treatment x place interaction and/ or treatment x season interaction . So the results of a series of experiments , performed over different places for different seasons with the same set of treatments,will have wider applicability .

We shall consider the simplest case of repetition of experiments of identical structure over a number of places ( it is the same for a number of seasons ). Let us consider randomized block experiments with t treatments in r blocks and conducted in p places. The analysis of the experiment in a place is based on the linear model . Before attempting a combined analysis for the p experiments ,it is necessary to perform the analysis for the p places separately and interpret the results separately .It may be of interest to find out whether differences among the treatments are the same in the different places so that a ‘ best ‘ treatment may be recommended for all the places, or whether different treatments are to be recommended for different places . The model for this combined analysis may be written as

Square-Root Transformation for Counts

stabilizes the variance more effectively.

Counts of rare events, such as number of defects or of accidents tend to be distributed approximately in poisson fashion.

Complete block designs become less efficient as the number of treatments increases,primarily because block size increases proportionally with the number of treatments,and the homogeneity of experimental plots within a large block is difficult to maintain.That is , the experimental error of a complete block design is generally expected to increase with the number of treatments.

An alternative set of designs for single –factor experiments having a large number of treatments is the incomplete block design.As the name implies, each block in an incomplete block design does not contain all treatments and a reasonably small block size can be maintained even if the number of treatments is large.With smaller blocks,the homogeneity of experimental units in the same block is easier to maintain and a higher degree of precision can generally be expected.

Introduction

As a chief feature of RCBD, formation of blocks is a necessity to achieve homogeneity of plots within each block so that an irrevelant source of variation existing to the error component could be removed for purposes of treatment comparisons. But quite frequently, in agricultural experiments, the fertility gradient varies in all directions so that the plots within a block in RCBD could still be heterogeneous. In order to control or remove this additional source of variation, one can think of extending the concept of blocking yet in another direction , orthogonal to the first direction, leading to a new design called Latin Square Design(LSD). In otherwords, if the blocking concept is one-dimensional in RCBD, it is two-dimensional in LSD. As a guiding principle for formation of two-dimensional blocks, it may be stated that each row-block and each column–block should remove as much variability as is possible from total variability so that error component becomes smaller. The chief restrictive features of LSD are:

The split-split plot design is an extension of the split-plot design to accommodate a third factor .It is uniquely suited for a three –factor experiment where three different levels of precision are desired for the various effects. Each level of precision is assigned to the effects associated with each of the three factors. This design is characterized by two important features :

1. There are three plot sizes corresponding to the three factors, namely, the largest plot (main plot) for the main-plot factor, the intermediate plot (sub-plot) for the subplot factor, and the smallest plot (sub-sub plot ) for the sub-subplot factor.
2. There are three levels of precision, with the main-plot factor receiving the lowest degree of precision and the sub-subplot factor receiving the highest degree of precision.

The method of analysis is entirely analogous to that for the case of 2 factors. The analysis consists of 3 parts, between whole plots, between split plots within whole plots,between split-split plots within split plots, each part being put on the basis of a split-split plot in order that the parts may be combined into one complete analysis.

Introduction

The split-plot design is specifically suited for a two-factor experiment that has more treatments than can be accommodated by a RCBD. In a split-plot design,one of the factors is assigned to the main plot. The assigned factor is called the main-plot factor. The main plot is divied into subplots to which the second factor ,called the subplot factor, is assigned. Thus, each mainplot becomes a block for the subplot treatments (i.e the levels of the subplot factor). The split-plot design is profitably employed under the following situations.

1. An experimenter may have already possessed some knowledge about the main effect of a certain factor so that his interest lies in estimating the interaction effect of this factor with some other more important factor in whose main effect also he is equally interested. In either case he wants to estimate the latter two effects with greater precision for which he is prepared to sacrifice the precision in estimating the first mainfactor.
2. The second common type of situation when the split-plot design is automatically suggestive is the difficulties in the execution of other design. For instance, if ploughing is one of the factors of interest,then one cannot have different depths of ploughing in different plots scattered randomly apart. Similarly, if different levels of irrigation are chosen,then random distribution of these levels in an ordinary experiment may involve difficulties in the practical execution of such plans. This difficulty may,however, be offset partly by having strips of plots (in one unit of block,say), all treated alike ;receiving the same level of irrigation with different depths of ploughing; or different levels of irrigation with same depth of ploughing. Different levels of irrigation or different depths of ploughing can,however,be randomly distributed over such strips.
3. The third situation in which the experimenter may adopt a split-plot design is this. A particular factor (factors) under investigation exhibits large treatment differences which can be easily detected even in bigger plots,while a second factor (factors) requires comparatively smaller plots to detect smaller treatment differences with higher precision. Then the first factor will be tested in whole plots and the second factor whose treatment differences are small will be tested in small plots or subplots.

Introduction

In many of the experimental designs considered previously like CRD and RCBD ,the main feature was to compare varieties,methods of cultivation,different kinds of fertilizers, etc. In general, in such experiments, only one factor is allowed to vary at a time, while all other factors known to affect the response are generally controlled. Such experiments are called ‘Simple’, or ‘Classical’ experiments.

Biological organisms are simultaneously exposed to many growth factors during their lifetime. Because an organism’s response to any simple factor may vary with the level of the other factors, simple factor experiments are often criticized for their narrowness. Indeed, the result of a single-factor experiment is, strictly speaking, applicable only to the particular level in which the other factors were maintained in the trial. But there are numerous occasions, especially in agriculture and animal experiments, where the main interest of an investigator does not lie with the effect of a single factor at a time but lies with simultaneous influence of many factors. For example, the interest of an investigator may not be in merely knowing the effect of spacing on the yield of a certain crop, but his interest would lie in finding out the simultaneous effect of both spacing and method of fertilizer application, that is, whether along with spacing, split dose of fertilizer at periodical intervals would be more beneficial than applying full recommended dose at one time. In order to answer this and many other questions, there are some special experiments called factorial experiments.

Introduction

In any experiment, for instance, a varietal trial or a treatment trial, the main purpose of the experimental design would be to detect the differences among the varieties or treatments. This assumes, as an obvious prerequisite that the experimental units, such as plots or animals, be as alike as possible so that differences observed in responses, such as yield in varietal trial, could be attributable to the varietal or treatment differences. But more often than not, this condition is not realized to a satisfactory degree in practice due to heterogeneity present in experimental units. In a field experiment, for instance, a big piece of land might be quite heterogeneous regarding soil fertility, moisture content, salinity, etc; so that experimental plots marked on this land would differ widely among themselves, though plots nearer to each other would be more alike or homogeneous than the plots scattered distant apart; also in the case of animal experiments, animals forming the experimental units might be heterogeneous regarding their ages , weights, genetic composition, etc. With such experimental units in the experiment, the variability produced in the observations will be comparatively high so that only large treatment differences are detectable, since small differences are obsecured by large error variability.

The randomized complete block design (RCBD), is perhaps the most widely used design of all experimental designs, mainly for its simplicity, flexibility and validity. The main objective of the design is either to control, remove or reduce the variability due to heterogeneity in experimental material, which is quite irrelevant for treatment comparisons. In CRD, the error variability as estimated from the residual sum of squares will be considerably high. The RCBD is a device introduced in this design for separating out the variability due to heterogeneity among experimental units from the variability due to all extraneous sources, thus purifying in one sense. The design is especially suitable for field experiments where the number of treatments is not large and the experimental area has a predictable productivity gradient.The primary distinguishing feature of the RCBD is the presence of blocks of equal size, each of which contains all the treatments.

Normal distribution :- A random variable x is said to be normally distributed with population mean u and standard deviation σ if it assumes the following distribution

Leafy vegetables are rich sources of provitamin-A, vitamin C and minerals like calcium, magnesium, iron, etc., They are the riches sources of roughes or fibres essential in human diet. The ICMR recommended dietary allowances of green leafy vegetables for adult women is 100g/day and men are 40g/day while for school children above 10 years it is 50g/day. Greens are rich in vitamins and minerals essential for healthy functioning of organs of body. Amaranth, beet leaf, spinach, fenugreek, etc., are the major leaf vegetables grown in India. In addition, a number of under-utilized annual crops are also grown as leaf vegetables in specific regions. Tender stems and leaves of a number of perennial crops are rich sources of vitamins and minerals and are used for cooking.

10.1. Amaranth (Amaranthus sp)

Amaranth is the most common leaf vegetable grown in India. Amarnath is an annual herb with erect growth and scarce to profusely branching habit. Stem is succulent and green or purple or mixed shades of these two. There are two sections in Amaranthus, viz., Amaranthus and Blitopsis. Majority of leaf cultivars grown in India belong to Amaranthus tricolor. Among the several kinds of greens Amaranthus occupy a special place because it has a large number of species grown in one or the other part of country.

Some of the important improved varieties released are CO-2 and CO-5 from TNAU, Coimbatore, Pusa Kiran, Pusa Kirti and Pusa Lal Choulia from IARI, New Delhi, Arka Arunima and Arka Suguna from IIHR, Bangalore. Amaranth are popular all over India by different names. While in northern parts it is popularly known as choulia, in south it is popularly called as keerai or cheera or koora or soppa. The general composition of amaranth is given below:

9.1. Onion (Allium cepa L.)

The onion (Allium cepa), which is also known as the bulb onion, or common onion is the most widely cultivated species of the genus Allium. It has been used as food since time immemorial and is an important vegetable all over the world. The genus Allium also contains a number of other species variously referred to as onions and cultivated for food, such as the Japanese bunching onion (A. fistulosum), Egyptian onion (A. proliferum), and Canada onion (A. canadense). The vast majority of cultivars of A. cepa belong to the “common onion group” (A. cepa var. cepa) and are usually referred to simply as “onions”. The Aggregatum Group of cultivars (A. cepa var. aggregatum) includes both shallots and potato onions. Onion is suggested to have been originated in Asia, particularly Pakistan and Iran.

China is the largest onion producer in the world followed by India. Largest area under onion is in India followed by China. The major onion producing state are Maharashtra, Karnataka, Madhya Pradesh, Rajasthan, Gujarat, Bihar, Andhra Pradesh, Tamil Nadu and Orissa.

Cultivars/Varieites: Onion varieties differ in size, colour of skin, pungency and maturation. The most popular varieties under cultivation are Agrifound Dark Red, Agrifound Light Red, Agrifound Red, Agrifound Rose, Arka Bindu, Arka Kalyan, Arka Niketan, Arka Pragati, Baswant 780, Brown Spanish, Co-1, Co-2 Co- 3, Co-4, Early Grano, Hisar II, Kalyanpur Red Round, MDU 1 N-2-4-1, N-53, N-257-9-1, Punjab 48 (S 48), Pusa Madhavi, Punjab Red Round, Punjab Selection, Pusa Ratnar, Pusa Red, Pusa White Flat, Pusa White Round, Udaipur 101, 102 & 103.

Leguminous vegetables include peas, French bean, Lima bean, broad bean, cowpea, hyacinth bean, winged bean etc. They belong to the family Fabaceae (Syn. Leguminosae). These are cultivated either as sole crop is sometimes as intercrop. In some areas they are used in backyard cultivation also. Most of them are short duration crops and are self pollinated.

8.1. Peas (Pisum sativum L.)

The pea (Pisum sativum L.) is a very common nutritioius vegetable grown in cool season throughout the world. It belongs to the family Fabaceae (Syn. Leguminaceae) and genus Pisum. A pea is most commonly the small spherical seed or the seedpod of the pod fruit Pisum sativum L. The pea cultivars are grouped into several groups based on shape of seed, plant height, maturity and use of pods. This crop is cultivated for its tender and immature pods for use as vegetable and mature dry pods for use as a pulse. In both the cases the seeds are separated and used as vegetable or pulse. The central Asia is regarded as the place of origin for all legumes including pea. Based on the genetic diversity, Central Asia, the Near East, Abyssinia and the Mediterranean is considered to be its centre of Origin. Cultivated garden pea is not seen in wild state and it might have been originated from wild field pea or other related species. In India it widely cultivated states of Uttar Pradesh, Bihar, Haryana, Punjab, Himachal Pradesh, Orissa and Karnataka. Followed by Madhya Pradesh, Himachal Pradesh, Assam and Jharkhand.

Cultivars/Varietie: Peas varieties are grouped based on maturity (early, mid season and late) plant height (Bush or dwarf, medium tall and tall). The major cultivars under cultivation in different parts of the country are Arkel, Bonneville, Harbhajan, FC-1, Arka Ajit, UN 53-6 (whole edible type), Jawahar Matar 1, Jawahar Matar 2, Jawahar Matar 3, Jawahar Matar 4, Jawahar Matar 5, Jawahar Peas 83, JP 4 (JM 6), JP 19, Lincoin, Mattar Ageta 6, Pantnagar Matar 2, Pant Uphar (IP 3), P 88, PRS 4,Ooty-1 and VL 3.

7.1. Okra or Bhindi (Abelmoschus esculentus L.)

Okra (Bhindi) is a member of Malvaceae family, earlier known as Hibiscus esculentus, and is an annual vegetable crop grown from seeds in tropical and subtropical parts of the world. Okra, also known as “lady finger” or “gumbo”, is a highly nutritious green edible pod vegetable. Botanically, this perennial flowering plant belongs to the mallow family but is grown as an annual. It is named scientifically as Abelmoschus esculentus. Okra originated in tropical and subtropical Africa and India is suggested to be the secondary centre of origin. There are four species under Abelmoschus genus which includes both cultivated and wild forms. They are A. esculentus, A. manihot, A. caillei and A. moschatus. In India, Okra is widely cultivated in states of Andhra Pradesh, West Bengal, Orissa, Bihar Uttar Pradesh, Karnataka, Assam West Bengal, Orissa, Gujarat and Bihar.

Cultivars/Varieties: Okra varieties differ in growth habit, height of plant, presence of purple pigmentation and ridges on fruit. The popular varieties under cultivation in different parts of the country are Arka Abhay, Arka Anamika, Azad Kranti, Co 1, MDU1, Gujarat Bhindi 1, Harbhajan Bhindi, Hisar Unnat, Parbhani Kranti, Perkins Long Green, Punjab 7, Punjab 8, Punjab Padmini, Pusa A 4, Pusa Makhmali, Pusa Sawani, Red Bhindi, TN Hybrid 8 and Varsha Uphar. Besides, a number of hybride from many private sector agencies/seed companies are marketed. Of these, Varsha, Vijay, Adhunik, Panchali, Hybrid No. 6,7 and 8, Nath Sobha, Supriya, Sungro 35, Aroh 1, - 2, -3, -9 and are more popular.

Uses

Different parts of the plant are used for different purposes. Abelmoschus moschatus Medik. Leaves and seeds are considered as valuable traditional medicine. Abelmoschus moschatus is also called ‘musk okra’ a medicinal plant belonging the same family. The leaves and new shoots of this plant is also used as vegetable. The aromatic seeds of this plant are aphrodisiac, ophthalmic, cardio tonic, antispasmodic and used in the treatment of and intestinal complaints and anxiety.

6.1. Potato (Solanum tuberosum L.)

Potato, Solanum tuberosum, is a starchy, tuberous crop belonging to the Solanaceae family. The name potato originally referred to a type of sweet potato, batata, in Spanish. Potatoes are occasionally referred to as “Irish potatoes” or “white potatoes” in the United States, to distinguish them from sweet potatoes. The potato was believed to be first domesticated in the region of southern Peru and extreme northwestern Bolivia between 8000 to 5000 BC. The potato diffused widely after 1600, becoming a major food resource in Europe and East Asia. Greater geographic mobility of farmers led to the rapid spread of potato cultivation throughout China, and India. China is now the world’s largest potato producer and nearly one third of the world’s potatoes are produced in China and India.

Today potato is the fourth major food crop after rice, wheat and maize in the world. In India potato is a very important crop and are mainly produced in the states of Uttar

Cultivars/Varieties: Most of the improved potato varieties were developed by CPRI, Kufri, Shimla. Most of the earlier varieties released as clonal selections derived from foreign varieties have been replaced with high yielding new varieties from the same institute. The popular varieties under cultivation now are Kufri Sindhuri, Kufri Chandramukhi, Kufri Jyothi, Kufri Lauvkar, Kufri Muthu, Kufri Dewa, Kufri Badshah, Kufri Bahar, Kufri Lalima, Kufri Swarna, Kufri Jawahar, Kufri Ashoka, Kufri Megha, Kufri Sutlej, Kufri Pukhraj, Kufri Chipsona-1, Kufri Chipsona-2 and Kufri Giriraj.

Uses

Potatoes are used in different ways like boiled, fried, baked and roasted. Potatoes are used to brew alcoholic beverages such as vodka, potcheen, or akvavit.They are also used as food for domestic animals. Potato starch is used in the food industry as, for example, thickeners and binders of soups and sauces, in the textile industry, as adhesives, and for the manufacturing of papers and boards. Many companies are exploring the possibilities of using waste potatoes to obtain polylactic acid for use in bioplastic products; other research projects seek ways to use the starch as a base for biodegradable packaging. Potato skins, along with honey, are used in folk medicine for burns in India. Burn centers in India have experimented with the use of the thin outer skin layer to protect burns while healing. The potato is best known for its carbohydrate content, which is in the form of starch. Because of its high starch content, it is a staple food in several parts of world including in some parts of India. A small but significant portion of this starch is resistant to digestion by enzymes in the stomach and small intestine, and so reaches the large intestine essentially intact, thereby, increasing its physiological significance. Besides these the potato also provides various other nutritional constituents to the body. Potato is also processed into various products like chips, powder, pappad, savory items.

Carrot, radish, turnip and beet root are major root crops grown in India. In addition, root crops like rutabaga, parsnip, parsley, chervil and celeriac are grown in a limited scale in different parts of the world. There are several other roots and modified underground plant parts that grow in forests and consumed by tribes, but they are not commercially cultivated. Carrot, radish, turnip and beet root are generally consumed as cooked vegetables or fresh salads or as pickled vegetables.

5.1. Carrot

Carrots belong to the Umbelliferae family, named after the umbrella-like f lower clusters that plants in this family produce. As such, carrots are related to parsnips, fennel, parsley, anise, caraway, cumin and dill. Carrot, Daucus carota L. is believed have been primarily originated in Afghanistan, South western Asia and Mediterranean region. Daucus carota ssp. Carota is the most common wild form in Europe and South West Asia, and the present day cultivated carrots have most probably originated from this sub-species.

Haryana, Andhra Pradesh, Punjab and Tamil Nadu, Karnataka, Uttar Pradesh and Assam are the major producers of carrot in India.

Cultivars/Varieties: Varieties with long, orange coloured and smooth roots are preferred in India. Both indigenous and exotic varieties having different root length, shape and colour are grown. Temperate or European type varieties are Nantes, Half long, Early Nantes, Chantenay, Chaman, Pusa Yamadagni and Ooty-1, which require low temperature of 4-8°C for flowering. Tropical or Asiatic type varieties do not require low temperature for flowering and can be grown in plains also. The varieties belonging to this group are Pusa Kesar, Pusa Meghali and Hisar Gairic. Some varieties like Gold King, Indian Kuroda and Super Kuroda are also marketed by private seed companies.