Episodes of insect life / By Acheta Domestica.

2

Le Volvox.

3

Die Zelle und die Gewebe. Grundzüge der Allgemeinen Anatomie und Physiologie.

1

A determinação dos números de indivíduos mínimos necessários na experimentação genética

The main object of the present paper consists in giving formulas and methods which enable us to determine the minimum number of repetitions or of individuals necessary to garantee some extent the success of an experiment. The theoretical basis of all processes consists essentially in the following. Knowing the frequency of the desired p and of the non desired ovents q we may calculate the frequency of all possi- ble combinations, to be expected in n repetitions, by expanding the binomium (p-+q)n. Determining which of these combinations we want to avoid we calculate their total frequency, selecting the value of the exponent n of the binomium in such a way that this total frequency is equal or smaller than the accepted limit of precision n/pª{ 1/n1 (q/p)n + 1/(n-1)| (q/p)n-1 + 1/ 2!(n-2)| (q/p)n-2 + 1/3(n-3) (q/p)n-3... < Plim - -(1b) There does not exist an absolute limit of precision since its value depends not only upon psychological factors in our judgement, but is at the same sime a function of the number of repetitions For this reasen y have proposed (1,56) two relative values, one equal to 1-5n as the lowest value of probability and the other equal to 1-10n as the highest value of improbability, leaving between them what may be called the "region of doubt However these formulas cannot be applied in our case since this number n is just the unknown quantity. Thus we have to use, instead of the more exact values of these two formulas, the conventional limits of P.lim equal to 0,05 (Precision 5%), equal to 0,01 (Precision 1%, and to 0,001 (Precision P, 1%). The binominal formula as explained above (cf. formula 1, pg. 85), however is of rather limited applicability owing to the excessive calculus necessary, and we have thus to procure approximations as substitutes. We may use, without loss of precision, the following approximations: a) The normal or Gaussean distribution when the expected frequency p has any value between 0,1 and 0,9, and when n is at least superior to ten. b) The Poisson distribution when the expected frequecy p is smaller than 0,1. Tables V to VII show for some special cases that these approximations are very satisfactory. The praticai solution of the following problems, stated in the introduction can now be given: A) What is the minimum number of repititions necessary in order to avoid that any one of a treatments, varieties etc. may be accidentally always the best, on the best and second best, or the first, second, and third best or finally one of the n beat treatments, varieties etc. Using the first term of the binomium, we have the following equation for n: n = log Riim / log (m:) = log Riim / log.m - log a --------------(5) B) What is the minimun number of individuals necessary in 01der that a ceratin type, expected with the frequency p, may appaer at least in one, two, three or a=m+1 individuals. 1) For p between 0,1 and 0,9 and using the Gaussean approximation we have: on - ó. p (1-p) n - a -1.m b= δ. 1-p /p e c = m/p } -------------------(7) n = b + b² + 4 c/ 2 n´ = 1/p n cor = n + n' ---------- (8) We have to use the correction n' when p has a value between 0,25 and 0,75. The greek letters delta represents in the present esse the unilateral limits of the Gaussean distribution for the three conventional limits of precision : 1,64; 2,33; and 3,09 respectively. h we are only interested in having at least one individual, and m becomes equal to zero, the formula reduces to : c= m/p o para a = 1 a = { b + b²}² = b² = δ2 1- p /p }-----------------(9) n = 1/p n (cor) = n + n´ 2) If p is smaller than 0,1 we may use table 1 in order to find the mean m of a Poisson distribution and determine. n = m: p C) Which is the minimun number of individuals necessary for distinguishing two frequencies p1 and p2? 1) When pl and p2 are values between 0,1 and 0,9 we have: n = { δ p1 ( 1-pi) + p2) / p2 (1 - p2) n= 1/p1-p2 }------------ (13) n (cor) We have again to use the unilateral limits of the Gaussean distribution. The correction n' should be used if at least one of the valors pl or p2 has a value between 0,25 and 0,75. A more complicated formula may be used in cases where whe want to increase the precision : n (p1 - p2) δ { p1 (1- p2 ) / n= m δ = δ p1 ( 1 - p1) + p2 ( 1 - p2) c= m / p1 - p2 n = { b2 + 4 4 c }2 }--------- (14) n = 1/ p1 - p2 2) When both pl and p2 are smaller than 0,1 we determine the quocient (pl-r-p2) and procure the corresponding number m2 of a Poisson distribution in table 2. The value n is found by the equation : n = mg /p2 ------------- (15) D) What is the minimun number necessary for distinguishing three or more frequencies, p2 p1 p3. If the frequecies pl p2 p3 are values between 0,1 e 0,9 we have to solve the individual equations and sue the higest value of n thus determined : n 1.2 = {δ p1 (1 - p1) / p1 - p2 }² = Fiim n 1.2 = { δ p1 ( 1 - p1) + p1 ( 1 - p1) }² } -- (16) Delta represents now the bilateral limits of the : Gaussean distrioution : 1,96-2,58-3,29. 2) No table was prepared for the relatively rare cases of a comparison of threes or more frequencies below 0,1 and in such cases extremely high numbers would be required. E) A process is given which serves to solve two problemr of informatory nature : a) if a special type appears in n individuals with a frequency p(obs), what may be the corresponding ideal value of p(esp), or; b) if we study samples of n in diviuals and expect a certain type with a frequency p(esp) what may be the extreme limits of p(obs) in individual farmlies ? I.) If we are dealing with values between 0,1 and 0,9 we may use table 3. To solve the first question we select the respective horizontal line for p(obs) and determine which column corresponds to our value of n and find the respective value of p(esp) by interpolating between columns. In order to solve the second problem we start with the respective column for p(esp) and find the horizontal line for the given value of n either diretly or by approximation and by interpolation. 2) For frequencies smaller than 0,1 we have to use table 4 and transform the fractions p(esp) and p(obs) in numbers of Poisson series by multiplication with n. Tn order to solve the first broblem, we verify in which line the lower Poisson limit is equal to m(obs) and transform the corresponding value of m into frequecy p(esp) by dividing through n. The observed frequency may thus be a chance deviate of any value between 0,0... and the values given by dividing the value of m in the table by n. In the second case we transform first the expectation p(esp) into a value of m and procure in the horizontal line, corresponding to m(esp) the extreme values om m which than must be transformed, by dividing through n into values of p(obs). F) Partial and progressive tests may be recomended in all cases where there is lack of material or where the loss of time is less importent than the cost of large scale experiments since in many cases the minimun number necessary to garantee the results within the limits of precision is rather large. One should not forget that the minimun number really represents at the same time a maximun number, necessary only if one takes into consideration essentially the disfavorable variations, but smaller numbers may frequently already satisfactory results. For instance, by definition, we know that a frequecy of p means that we expect one individual in every total o(f1-p). If there were no chance variations, this number (1- p) will be suficient. and if there were favorable variations a smaller number still may yield one individual of the desired type. r.nus trusting to luck, one may start the experiment with numbers, smaller than the minimun calculated according to the formulas given above, and increase the total untill the desired result is obtained and this may well b ebefore the "minimum number" is reached. Some concrete examples of this partial or progressive procedure are given from our genetical experiments with maize.

Adubação da mandioca (Manihot utilissima Pohl.) I: ensaio em areia lavada (Nota prévia)

This paper deals with the preliminary results of a sand culture experiment carried out to obtain physiological bases to study the fertilization of cassava in the State of São Paulo. On the other hand, the authors are interested in the possible influence of mineral nutrients in the quantity and quality of starch. Cassava (Manihot utilissima Pohl.), "Branca de Sta. Catarina" variety, was grown under the following treatments: NO PO KO, NO P1 K1, N1 P0 Kl, NI P1K0, N2 p1 Kl N1 P2 K1 and N1 P1 K2. A striking response to phosphorus was observed among the treatments. However, once secured the necessary phosphoric level to the plant, the production becomes limited by nitrogen; in other words, increase in yield can be accomplished only by raising the nitrogenous level. The present results suggest that the remarkable effects of phosphates applied to cassava cultures in the State of São Paulo are due not only to the poor quality of our soils, as far phosphorus is concerned: we are facing a positive physiological response showed by the plant.

Estudos sôbre a alimentação mineral da mandioca (Manihot utilissima Pohl.)

1. The present work was carried out to study the effects of mineral nutrients in the yield as well as in the composition of cassava roots. The variety "Branca de Sta. Catarina" was grown by the sand culture method, the following treatments being used: N0 P0 K0, N0 P1 Kl, N1 P0 K1, N2 P1 K0, N2 P1 K1, N1 P2 K1, and N1 P1 K2, where the figures 0, 1, and 2 denote the relative proportion of a given element. The nutrients were given as follows: N = 35 grams of ammonium nitrate per pot loaded with 120 pounds of washed sand; P1 = 35 grams of monocalcium phosphate; Kl = 28 grams of sulfate of potash. Besides those fertilizers, each pot received 26 grams of magnesium sulfate and weekly doses of micronutrients as indicated by HOAGLAND and ARNON (1939). To apply the macronutrients the total doses were divided in three parts evenly distributed during the life cycle of cassava. 2. As far yield of roots and foliage are concerned, there are a few points to be considered: 2.1. the most striking effect on yield was verified when P was omitted from the fertilization; this treatment gave the poorest yields of the whole experiment; the need of that element for the phosphorylation of the starchy reserves explains such result; 2.2. phosphorus and nitrogen, under the experimental conditions, showed to be the most important nutrients for cassava; the effect of potassium in the weight of the roots produced was much less marked; it is noteworthy to mention, that in absence of potassium, the roots yield decreased whereas the foliage increased; as potassium is essential for the translocation of carbohydrates it is reasonable to admit that sugars produced in the leaves instead of going down and accumulate as starch in the roots were consumed in the production of more green matter. 3. Chemical analyses of roots revealed the following interesting points: 3.1. the lack of phosphorus brought about the most drastic reduction in the starch content of the roots; while the treatment N1 P1 K1 gave 32 per cent of starch, with NI PO Kl the amount found was 25 per cent; this result can be explained by the requirement of P for the enzymatic synthesis of starch; it has to be mentioned that the decrease in the starch content was associated with the remarkable drop in yield observed when P was omitted from the nutrient medium; 3.2. the double dosis of nitrogen in the treatment N2 P1 K1, gave the highest yields; however the increase in yield did not produce any industrial gain: whereas the treatment N1 P1 K1 gave 32 per cent of starch, by raising the N level to N2, the starch content fell to 24 per cent; now, considering the total amount of starch present in the roots, one can see, that the increase in roots yield did not compensate for the marked decrease in the starch content; that is, the amount of starch obtained with N1 P1 K1 does not differ statistically from the quantity obtained with N2 P1 K1; as far we know facts similar to this had been observed in sugar beets and sugar cane, as a result of the interaction between nitrogen and sugar produced; the biochemical aspect of the problem is very interesting: by raising the amount of assimilable nitrogen, instead of the carbohydrates polymerize to starch, they do combine to the amino groups to give proteinaceous materials; actually, it did happen that the protein content increased from 2.91 to 5.14 per cent.

Adubação em "torrão paulista" de Eucalyptus Saligna SM

Num ensaio de adubação com N, P, K e estêrco (E) de mudas de eucalipto (Eucalyptus saligna Sm.) em "torrão paulista" nos viveiros da Cia. Paulista de Estrada de Ferro, em Rio Claro, SP, foi usado um delineamento fatorial de 3x3x3x2, com resultados estatisticamente significativos para N, P e estêrco. As alturas médias das mudas, em centímetros, 3(1/2) meses após a repicagem para os torrões, foram as seguintes. N0 42,4 ± 1,5 P0 56,4 ± 1,5 E0 54,9 ± 1,2 N1 62,8 ± 1,5 P1 58,4 ± 1,5 E1 64,0 ± 1,2 N2 73,2 ± 1,5 P2 63,6 ± 1,5 As médias de algumas combinações interessantes de tratamentos são dadas a seguir, em centímetros. N0PoK0Eo 41,3 ± 6,2 N2P2K0E1 83,0 ± 6,2 N2P0K0E0 59,6 ± 6,2 N2P2K2E1 87,4 ± 6,2 N2P2K0E0 64,0 ± 6,2

Revue et magasin de zoologie pure et appliquée.

ser. 2, v. 12 (1860)

Revue et magasin de zoologie pure et appliquée.

ser. 2, v. 7 (1855)

Magasin de zoologie, d'anatomie comparée et de palaeontologie.

ser. 2, v. 7 (1845)

Magasin de zoologie, d'anatomie comparée et de palaeontologie.

ser. 2, v. 1-3 (1831-41)

Mineralogia da fração argila de perfis de solos da série Piracicaba

O presente trabalho teve por finalidade o estudo mineralógico, da fração argila, da série Piracicaba (RANZANI et al. 9), pertencente à unidade de mapeamento Podzólico Vermelho Amarelo - variação Piracicaba (COMISSÃO DE SOLOS, 2). Foram coletados, na área de ocorrência da série Piracicaba, quatro perfis de solos, designados por perfis P1, P2, P3 e P4. As amostras dos horizontes foram colhidas a partir da superfície do solo até a rocha. A fração argila foi separada por sedimentação, sendo posteriormente, dividida em duas subfrações (centrifugação): 2 a 0,2 mícron e menor que 0,2 mícron, argila grossa e fina, respectivamente. O material obtido nestas duas frações, sofreu determinações químicas (% de K2O e capacidade de troca de cátions) e determinações de raio - X (obtenção de difratogramas, com auxílio do contador Geiger, e filmes, pelo método do pó). Através destes resultados, foi efetuado o reconhecimento dos minerais de argila assim como estimativa semiquantitativa. A análise mineralógica das frações argila grossa e fina, referentes à natureza e à quantidade dos minerais de argila indica o seguinte: o teor de ilita, na fração argila grossa é sempre maior do que 10%, sendo que, em certos horizontes, apresenta teor de 30% e mesmo 40%. A montmorilonita e os minerais de 14 A normalmente ocorrem com valores inferiores a 10%. A caolinita é o mineral dominante nas duas frações argila, com teores sempre acima de 40%.

Mineralogia da fração argila de perfis de solos da série Ibitiruna

O presente trabalho teve por finalidade o estudo minera lógico, da fração argila, da série Ibitiruna (RANZANI et al. 9), pertencente a unidade de mapeamento Podzólico Vermelho Amarelo - variação Laras (COMISSÃO DE SOLOS 1). Foram coletados três perfis de solos, pertencente a série Ibitiruna, designados por perfis P1, P2 e P3. As amostras dos horizontes foram colhidas a partir da superfície do solo até a rocha. A fração argila foi separada por sedimentação, sendo posteriormente, dividida em duas subfrações (centrifugação): 2 a 0,2 mícron e menor que 0,2 mícron, argila grossa e fina respectivamente. O material obtido nestas duas frações, sofreu determinações químicas (capacidade de troca de cátions) e determinações de raio-X (obtenção de difratogramas, com o auxílio do contador Geiger, e filmes, pelo método do pó). Através dêstes resultados, foi efetuado o reconhecimento dos minerais de argila assim como estimativa semiquantitativa. A análise mineralógica das frações argila grossa e fina, referentes à natureza e à quantidade dos minerais de argila indica o seguinte: a caolinita é o mineral dominante nas duas frações argila, com teores sempre acima de 40%; a montmorilonita e os minerais do grupo de 14 Anormalmente ocorrem com valôres inferiores a 10%.

Revue et magasin de zoologie pure et appliquée.

ser. 2, v. 8 (1856)