Plant Breeding

The nature of code: Why is it

Many find genetics, as a field of science on its own, charming. Many more are excited to learn about the science that fits seamlessly into complexity driven life of organisms, providing explanation for natural phenomena at both micro-evolutionary and macro-evolutionary scales. But only few find fascination with its deep running concepts, going down to more fundamental physical theories. This article tries to at least expose, if not laid satisfying argument, to some of fundamental questions in genetics concerning nature of code (mostly chemical behaviour). In particular, following are some of the questions I plan to touch upon (Credit goes to a student of mine who posed these questions one evening and left me pondering on details):

Correlation and pathway analysis with path diagrams

Background

Correlation study is one of the most extensively yet not fully appreciated topic. It forms the backbone of several other inferential studies. Path analysis, on a similar note, is a derived technique that explains directed dependencies among a set of variables. It is almost exactly a century old now and still finds uses in several fields of causal inference.

In oder to understand the process of causal inference (thought to be successor of path analysis), it is important to understand the basics about categories of variables. Below I have pointed out some of the concepts.

World production and grain composition of major cultivated species

Context

Out of crops raised for their seed/grains (listed under 35 species, by FAO; FAOSTAT, 2014), only 22 species are produced in substantial amounts. Species of graminae and leguminosae families alone account for about 85 percent of the total grain production. As presented here in Table 1.

Production

(\#tab:world-production)Global production of major cultivated crops
Crop Crop species World production^[Average of 2011 to 2014, FAOSTAT (2016)] (1000 t)
Poaceae
Maize Zea mays L. 950394
Rice Oryza sativa L. 733424
Wheat Triticum spp. 700828
Barley Hordeum vulgare L. 138252
Sorghum Sorghum bicolor (L.) Moench 58647
Millet^[May include members of other genera such as Pennisetum, Papspalm, Setoria and Echinochla] Panicum miliaceum L. 26528
Oat Avena sativa L. 22639
Rye Secale cereale L. 14906
Triticale X Triticosecale Wittm ex A. Camus 14653
Fabaceae
Soybean Glycine max (L.) Merrill 272426
Groundnut^[In the shell] Arachis hypogaea L. 41366
Bean^[Also includes other species of Phaseolus and, in some countries, Vigna species.] Phaseolus vulgaris L. 23898
Chickpea Cicer arietinum L. 12735
Pea, dry^[May include P. arvense (field pea).] Pisum sativum L. 11013
Cowpea Vigna unguiculata (L.) Walp. 6661
Lentil Lens culinaris Medikus 4831
Broad bean Vicia faba L. 4332
Pigeon pea Cajanus cajan L. Millsp. 4454
Others^[Rapeseed is in the Brassicaceae, sunflower and safflower are in the Asteraceae, and sesame is in Pedaliaceae.]
Rapeseed^[May include industrial and edible (canola) types, data from some countries includes mustard (Brassica juncea (L.) Czern, et Coss)] Brassica napus L., B campestris L. 67789
Sunflower Helianthus annuus L. 40931
Sesame Sesamum indicum L. 4738
Safflower Carthamus tinctoris L. 776

Grain composition

(\#tab:grain-comp)Global production of major cultivated crops
Crop Crop species Harvested unit Seed carbohydrate (g_per_kg) Seed oil (g_per_kg) Seed protein (g_per_kg)
Poaceae
Maize Zea mays L. Caryopsis 800 50 100
Rice Oryza sativa L. Caryopsis 880 20 80
Wheat Triticum spp. Caryopsis 750 20 120
Barley Hordeum vulgare L. Caryopsis^[Harvested grain usually includes the lemma and palea] 760 30 120
Sorghum Sorghum bicolor (L.) Moench Caryopsis 820 40 120
Millet^[May include members of other genera such as Pennisetum, Papspalm, Setoria and Echinochla] Panicum miliaceum L. Caryopsis 690 50 110
Oat Avena sativa L. Caryopsis^[Harvested grain usually includes the lemma and palea] 660 80 130
Rye Secale cereale L. Caryopsis 760 20 120
Triticale X Triticosecale Wittm ex A. Camus Caryopsis 594 18 131
Fabaceae
Soybean Glycine max (L.) Merrill Non-endospermic seed 260 170 370
Groundnut^[In the shell] Arachis hypogaea L. Non-endospermic seed 120 480 310
Bean^[Also includes other species of Phaseolus and, in some countries, Vigna species.] Phaseolus vulgaris L. Non-endospermic seed 620 20 240
Chickpea Cicer arietinum L. Non-endospermic seed 680 50 230
Pea, dry^[May include P. arvense (field pea).] Pisum sativum L. Non-endospermic seed 520 60 250
Cowpea Vigna unguiculata (L.) Walp. Non-endospermic seed 570 10 250
Lentil Lens culinaris Medikus Non-endospermic seed 670 10 280
Broad bean Vicia faba L. Non-endospermic seed 560 10 230
Pigeon pea Cajanus cajan L. Millsp. Non-endospermic seed 560 20 250
Others^[Rapeseed is in the Brassicaceae, sunflower and safflower are in the Asteraceae, and sesame is in Pedaliaceae.]
Rapeseed^[May include industrial and edible (canola) types, data from some countries includes mustard (Brassica juncea (L.) Czern, et Coss)] Brassica napus L., B campestris L. Non-endospermic seed 190 480 210
Sunflower Helianthus annuus L. Cypsela 480 290 200
Sesame Sesamum indicum L. Non-endospermic seed 190 540 200
Safflower Carthamus tinctoris L. Cypsela 500 330 140

References

Page 3 and 4, Seed Biology and Yield of Grain Crops, 2nd Edition

Color charts: An introductory review on applications to qualitative crop phenotyping

Background

Colorimetry is a fascinating topic to discuss. In conjunction with the patterns of a natural world (See this awesome video about fibonacci numbers and plants), colors could have mesmerizing feels. In this post and the follow-up article, we will discuss in details about colorimetric features of a universe made of plants, in particular, which are cultivated/adopted and have edible human values – the agricultural crops. Then again, there are quite a large number of agricultural species to deal with. So, we will be making a touch down on some common crop species, i.e. Pea (Pisum sativum, wild counterpart of the famous Lathyrus pea studied by Mendel) and Wheat (Triticum aestivum).