Seasonal changes in the pigment composition of needles of representatives of the genus spruce in the Nizhny Novgorod region

Изучали характер и масштаб сезонных изменений пигментного состава хвои разных видов ели (Picea A. Dietr.) в условиях интродукции в Нижегородскую область, выявляли содержание и баланс пластидных пигментов фотосинтеза. Объектами исследования выступали 13 видов ели, относящихся к аборигенам и экзотам: ель европейская (Picea abies (L.) H. Karst.); ель сибирская (Picea obovata Ledeb.); ель Глена (Picea glehnii (F. Schmidt) Mast.); ель белая (Picea glauca (Moench) Voss); ель шероховатая (Picea asperata Masters); ель черная (Picea mariana Mill., Britton, Sterns & Poggenburg); ель колючая форма серебристая (Picea pungens Engelm., f. argentea); ель колючая форма голубая (Picea pungens Engelm., f. glauca Regel); ель сербская (Picea omorika (Pančić) Purk.); ель Энгельмана (Picea engelmannii Parry ex Engelm.); ель колючая (Picea pungens Engelm.); ель аянская (Picea jezoensis (Siebold & Zucc.) Carrière); ель корейская (Picea koraiensis Nakai). Отбор проб осуществлен рендомизированно с соблюдением принципа единственного логического различия. Использовали спектрофотометр СФ-2000. Установлено, что содержание и соотношение пластидных пигментов в хвое динамично в течение года. Определена эффективность влияния фаз сезонного развития растений на характеристики пигментного состава: по содержанию хлорофилла-a – 18,86±0,32%; по содержанию хлорофилла-b – 21,26±0,31%; по сумме хлорофиллов – 16,13±0,33%; по каротиноидам – 37,43±0,25%; по доле хлорофилла-a – 39,74±0,24% и доле хлорофилла-b – 39,74±0,24%. Эффект влияния межвидовых различий по показателям содержания и соотношения разных форм хлорофилла и каротиноидов достоверен и в достаточной мере выравнен при максимуме 23,56±0,91%. При общих тенденциях в сезонной динамике представители рода ель обладают заметной видоспецифичностью пигментного состава. We studied the nature and scale of seasonal changes in the pigment composition of needles of different spruce species (Picea A. Dietr.) under the conditions of introduction to the Nizhny Novgorod region, and revealed the content and balance of photosynthetic plastid pigments. The objects of the study were 13 species of spruce belonging to aborigines and exotics: Norway spruce (Picea abies (L.) H. Karst.); Siberian spruce (Picea obovata Ledeb.); Glen spruce (Picea glehnii (F. Schmidt) Mast.); white spruce (Picea glauca (Moench) Voss); Dragon spruce (Picea asperata Masters); black spruce (Picea mariana Mill., Britton, Sterns & Poggenburg); silver prickly spruce (Picea pungens Engelm., f. argentea); blue prickly spruce (Picea pungens Engelm., f. glauca Regel); Serbian spruce (Picea omorika (Pančić) Purk.); Engelman spruce (Picea engelmannii Parry ex Engelm.); Blue spruce (Picea pungens engelm.); Ayan spruce (Picea jezoensis (Siebold & Zucc.) carrière); Korean spruce (Picea koraiensis Nakai). Sampling was carried out in a randomized manner, following the principle of a single logical difference. A spectrophotometer SF-2000 was used. It was found that the content and ratio of plastid pigments in conifers is dynamic throughout the year. The effectiveness of the influence of the phases of seasonal plant development on the characteristics of the pigment composition is determined: by the content of chlorophyll-a-18.86±0.32%; by the content of chlorophyll-b-21.26±0.31%; by the sum of chlorophylls-16.13±0.33%; by carotenoids – 37.43±0.25%; by the proportion of chlorophyll-a – 39.74±0.24% and the proportion of chlorophyll-b – 39.74±0.24%. The effect of interspecific differences in the content and ratio of different forms of chlorophyll and carotenoids is significant and sufficiently equalized at a maximum of 23.56±0.91%. With General trends in seasonal dynamics, representatives of the spruce genus have a noticeable species-specific pigment composition.

Prediction of Needle Chlorophyll Model with Different Leaf Ages Based on BP Neural Network and PLSR

BackgroundTo explore the changes of chlorophyll content in needles of different leaf ages of Picea koraiensis Nakai of different specifications, the study compared the prediction accuracy changes of chlorophyll in needles of Picea koraiensis Nakai by two modeling methods: the BP neural network and partial least squares regression (PLSR) methods. The effects of different spectral pre-processing and characteristic band selection methods on the performance accuracy of the model were tested, and the optimal combination model was selected to predict forest growth status and community structure productivity through the physiological and biochemical characteristics of needles at different leaf ages. Results1) the spectral pre-processing method could avoid systematic errors and eliminate background values; 2) the accuracy of the needle chlorophyll fitting model with different leaf ages was much higher than that of mixed needle chlorophyll model, verifying that needle chlorophyll with different leaf ages could better estimate the annual growth and examine the growth status of Picea koraiensis Nakai; 3) the accuracy of the BP neural network model was significantly higher than that of the PLSR model, with its R 2 above 0.95, and the validation set’s R 2 above 0.86; and 4) the fitting accuracy of different leaf age needle chlorophyll models of the spectral pre-processing model, variable selection model, PLSR model and BP neural network: triennial needles > annual and biennial needles. ConclusionsThe BP neural network method was more accurate than the PLSR method in predicting pigment content model. In the process of model fitting, it was found that the pigment model fitted by fine classification of needles improves the accuracy of the model, which provides the basis and theoretical support for the establishment of the model by combining remote sensing technology with stoichiometry methods in the future.